Online First

Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes/issues, but are citable by Digital Object Identifier (DOI).
Display Method:
Integrating High-resolution Bioassay Profiling with Affinity-based Ligand Fishing for Unveiling Galloylated Derivatives as Novel Catechol-O-methyltransferase Inhibitors in Paeonia lactiflora Pall.
Jiaming YUAN, Zhuoping ZHENG, Zhongkang WANG, Hao TIAN, Lingling XI, Jacques CROMMEN, Tingting ZHANG, Jincai WANG, Zhengjin JIANG
, Available online  , doi: 10.1016/j.jpha.2025.101449
Abstract(8) HTML Full Text PDF(1)
Abstract:
Catechol-O-methyltransferase (COMT) inhibition is a critical therapeutic strategy for Parkinson’s disease (PD), yet clinical inhibitors face limitations in bioavailability and hepatotoxicity, driving demand for novel natural scaffolds. In this study, we developed an integrated analytical platform by coupling high-resolution bioassay profiling (HRBP) and affinity-based ligand fishing system to effectively characterize bioactive compounds targeting COMT in Paeonia lactiflora Pall. (the most frequently used core herb in tradition Chinese medicine prescriptions for PD treatment). Parallel High-performance liquid chromatography with diode-array detection and tandem mass spectrometry (HPLC-DAD-MS/MS) coupled with nanofractionation enabled real-time bioactivity mapping via 384-well COMT inhibition assays, while semi-preparative liquid chromatography was employed to further identify co-eluted components. HRBP and immobilized COMT ligand fishing identified 16 and 21 candidates, respectively, with 5 overlapping bioactive markers. Notably, the potent inhibitors galloylpaeoniflorin (IC50 = 16.2 ± 3.4 μM) and 1,2,3,4,6-O-pentagalloylglucose (IC50 = 3.1 ± 0.5 μM) exhibited comparable potency to the positive control morin (IC50 = 10.1 ± 0.7 μM). Molecular docking results further revealed the critical interactions and binding sites between the active compounds and COMT. The validated platform demonstrates significant potential for rapid discovery of plant-derived enzyme inhibitors, bridging advanced separation, bioactivity screening, and mechanistic validation in neurodegenerative therapeutic development.
Polydatin for Treating Spinal Cord Injury: Multiple Mechanisms and Challenges
Zhishuo Wang, Jiaming Zhang, Longyu Li, Yuhao Zhang, Haoyu Shen, Chunfeng Shang, Zikuan Leng, Guowei Shang, Hongwei Kou, Keya Mao, Hao Han, Songfeng Chen, Hongjian Liu
, Available online  , doi: 10.1016/j.jpha.2025.101451
Abstract(8) HTML Full Text PDF(1)
Abstract:
Spinal cord injury (SCI) is a serious neurological system disease. After SCI, a series of cascade reactions can cause irreversible damage, with a high disability rate and mortality rate. The complexity of the pathological mechanism of SCI limits the efficacy of various traditional therapies, and it is urgent to find new therapeutic means. In recent years, the method of extracting effective components from natural Chinese herbs for treating diseases has attracted widespread attention. Polydatin (PD) is an active ingredient extracted from Polygonum cuspidatum and its structure is similar to the traditional drug resveratrol. Sufficient studies have proved that PD plays anti-inflammatory, antioxidant, anti-apoptotic and neuroprotective roles in the treatment of multisystem diseases. These effects are also significant in the treatment of SCI. Based on the structural differences between PD and resveratrol, this paper illustrates the feasibility of PD in the treatment of SCI, and systematically expounds the pathophysiological process of SCI and the molecular mechanism of PD in the treatment of SCI. Furthermore, this article discusses feasible measures to improve the bioavailability of PD, summarizes the application of new drug delivery systems in PD, and analyzes the challenges and prospects of PD in SCI treatment.
PFKM promotes chemoresistance in lung adenocarcinoma by regulating RAB8B mediated exosome release
Qiang Wang, Qiyao Nong, Junguo Zang, Meiyu Gao, Ying Zhang, Xinyuan Hao, Yuan Tian, Fengguo Xu, Pei Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101450
Abstract(14) HTML Full Text PDF(0)
Abstract:
Lung adenocarcinoma (LUAD), the most widely existing subtype of non-small cell lung cancer (NSCLC), is a leading cause of cancer-related mortality, characterized by challenging early diagnosis, high rates of recurrence and metastasis, and poor prognosis. Chemotherapy remains the primary treatment for advanced LUAD, but its effectiveness is often hindered by the development of chemoresistance. In this study, a targeted metabolomics method unveiled a marked up-regulation of glycolysis in chemotherapy-resistant LUAD cells. Particularly, the ratio of fructose 1,6-bisphosphate (FBP) to fructose 6-phosphate (F6P) reflected the activity of the rate-limiting enzyme Phosphofructokinase muscle isoform (PFKM) was significantly elevated. We further observed a significant increase in exosome release in chemotherapy-resistant cells. More importantly, it was found that the interaction between PFKM and exosomes plays a role in regulating chemoresistance in LUAD. Mechanistically, PFKM influences exosomes release by modulating Ras-related protein Rab-8B (RAB8B) expression, impacting apoptosis and glycolytic metabolism, thereby promoting chemoresistance. Furthermore, drug-resistant cells enhance chemoresistance in sensitive cells by releasing exosomes with heightened glycolytic activity. These findings highlight the crucial role of the PFKM-RAB8B axis in promoting chemoresistance, suggesting it as a potential therapeutic target for countering LUAD chemoresistance.
Novel Bioactive Peptides Targeting Keap1-Nrf2 Interaction for Combating UVA-Induced Skin Aging: Computational Discovery and Experimental Validation
Haiqiong Guo, Yueting Sun, Wenyu Shi, Rui Huang, Xiaobei Zhi, Qingsong Liu, Ping Zhao, Qingyou Xia
, Available online  , doi: 10.1016/j.jpha.2025.101446
Abstract(20) HTML Full Text PDF(0)
Abstract:
Ultraviolet A (UVA)-induced skin aging poses a significant threat to skin health and aesthetics, yet effective and biosafe therapeutic interventions remain scarce. This study focused on identifying bioactive peptide inhibitors targeting the Kelch-like ECH-associated protein 1 (Keap1)-nuclear factor erythroid 2-related factor 2 (Nrf2) protein-protein interaction (PPI) to counteract UVA-induced skin aging. Using computational virtual screening, we identified two high-affinity, low-toxicity peptides, Seq1 and Seq3, which effectively activated the Nrf2-antioxidant response element (ARE) pathway. This activation led to the upregulation of antioxidant genes and significantly reduced oxidative stress. Additionally, these peptides inhibited the mitogen-activated protein kinase (MAPK) and nuclear factor kappa-B (NF-κB) signaling pathways, thereby reducing inflammation and suppressing the expression of matrix metalloproteinases (MMPs), key contributors to skin aging. In vivo studies demonstrated that Seq1 and Seq3 effectively prevented UVA-induced epidermal thickening, collagen degradation, and the upregulation of pro-inflammatory cytokines in mouse models. Our results underscore the therapeutic potential of Seq1 and Seq3, particularly Seq3, as novel bioactive peptides targeting the Keap1-Nrf2 PPI for combating UVA-induced skin aging, offering promising avenues for skincare and healthcare applications.
Enhancing polyreactivity prediction of preclinical antibodies through fine-tuned protein language models
Yuwei Zhou, Haoxiang Tang, Changchun Wu, Zixuan Zhang, Jinyi Wei, Rong Gong, Samarappuli Mudiyanselage Savini Gunarathne, Changcheng Xiang, Jian Huang
, Available online  , doi: 10.1016/j.jpha.2025.101448
Abstract(12) HTML Full Text PDF(0)
Abstract:
Therapeutic monoclonal antibodies (mAbs) have garnered significant attention for their efficacy in treating a variety of diseases. However, some candidate antibodies exhibit non-specific binding to off-target proteins or other biomolecules, leading to high polyreactivity, which can compromise therapeutic efficacy and cause other complications, thereby reducing the approval rate of antibody drug candidates. Therefore, predicting the polyreactivity risk of therapeutic mAbs at an early stage of development is crucial. In this study, we fine-tuned six pre-trained protein language models to predict the polyreactivity of antibody sequences. The most effective model, named PolyXpert, demonstrated a sensitivity (SN) of 90.10%, specificity (SP) of 90.08%, accuracy (ACC) of 90.10%, F1-score of 0.9301, Matthews correlation coefficient (MCC) of 0.7654, and an area under curve (AUC) of 0.9672 on the external independent test dataset. These results suggest its potential as a valuable in-silico tool for assessing antibody polyreactivity and for selecting superior therapeutic mAb candidates for clinical development. Furthermore, we demonstrated that fine-tuned language model classifiers exhibit enhanced prediction robustness compared with classifiers trained on pre-trained model embeddings. PolyXpert can be easily available at https://github.com/zzyywww/PolyXpert.
Polysaccharides self-healing hydrogel for skin regeneration
Nan Xu, Fanhe Meng, Binglun Zhang, Xing Yang, Haibo Wang, Fan Yang
, Available online  , doi: 10.1016/j.jpha.2025.101447
Abstract(29) HTML Full Text PDF(1)
Abstract:
Damaged skin is prone to infection and impaired healing, making efficient wound care materials critical. Polysaccharide-based self-healing hydrogels have demonstrated significant potential in skin regeneration due to their biocompatibility, biodegradability, and ability to mimic the extracellular matrix (ECM). This review summarizes the fabrication techniques, core polysaccharide materials, and challenges of these hydrogels. Hydrogel preparation primarily involves chemical cross-linking, physical cross-linking, and three-dimensional (3D) bioprinting. Chemical cross-linking confers high mechanical strength but limited self-healing capacity, while physical cross-linking enables rapid self-healing via dynamic non-covalent interactions, responsive to stimuli like pH and temperature. 3D bioprinting allows customizable tissue-like structures with precise control over cell distribution and bioactive molecule release. Key polysaccharides include alginate, chitosan, hyaluronic acid (HA), cellulose, and dextran. Alginate forms reversible networks via calcium ion cross-linking, suitable for wound dressings and tissue engineering. Chitosan, with amino and hydroxyl groups, exhibits antibacterial activity and promotes cell proliferation, widely used in infected wounds. HA achieves self-healing through dynamic covalent bonds, accelerating collagen deposition and angiogenesis. Cellulose derivatives employ boronic ester or Schiff base linkages for self-healing systems in injectable formulations. Dextran utilizes Diels-Alder reactions for self-healing under physiological conditions, ideal for drug delivery. Commercial products like HyStem® and Chitogel® have entered clinical use, integrating growth factors or antimicrobials to enhance wound healing. However, challenges persist, including insufficient mechanical strength, mismatched degradation rates with healing processes, long-term safety concerns, and scalability. Future directions focus on "smart" hydrogels, combined with clustered regularly interspaced short palindromic repeats (CRISPR) gene editing or artificial intelligence (AI)-optimized design, to enhance functionality and clinical translation.
Toward realistic pharmaceutical evaluation: Challenges in 3D-printed organ chip of vascularized tissue with microcirculation
Ling Wang, Ziyan Qiu, Yingjie Liu, Fei Wang, Dichen Li
, Available online  , doi: 10.1016/j.jpha.2025.101445
Abstract(19) HTML Full Text PDF(2)
Abstract:
Comparative analysis for optimal LSD1 inhibitors evaluation techniques:pros and cons
Qiange Yin, Congcong Ma, Xiaoying Zhao, Panjie Wang, Dandan Shen, Chenchen Ren, Baojin Wang, Feiyan Li, Yan Yang, Hui-Min Liu, Li Yang, Yi-Chao Zheng
, Available online  , doi: 10.1016/j.jpha.2025.101430
Abstract(39) HTML Full Text PDF(4)
Abstract:
Aberrant expression of lysine-specific demethylase 1 (LSD1) has been consistently implicated in a broad spectrum of malignancies, underscoring its relevance as a therapeutic target. Despite growing interest, the development of LSD1 inhibitors continues to face significant challenges, in part due to the enzyme’s dual role in catalysis and as a scaffolding protein within chromatin-remodeling complexes. Recent insights into the non-enzymatic functions of LSD1 have shifted the focus toward disrupting its protein–protein interactions, particularly with chromatin-modifying enzymes, as a complementary or alternative therapeutic strategy. In light of the limited systematic evaluation of available technologies, this work provides a critical overview and comparative analysis of current screening platforms and binding affinity assays, with particular attention to approaches capable of identifying LSD1 scaffold inhibitors. These efforts aim to accelerate the discovery of next-generation LSD1-targeted therapies with improved translational potential in oncology.
Artificial Intelligence and Computational Methods in Human Metabolism Research: A Comprehensive Survey
Manzhan Zhang, Yuxin Wan, Jing Wang, Shiliang Li, Honglin Li
, Available online  , doi: 10.1016/j.jpha.2025.101437
Abstract(56) HTML Full Text PDF(9)
Abstract:
Understanding the metabolism of endogenous and exogenous substances in the human body is essential for elucidating disease mechanisms and evaluating the safety and efficacy of drug candidates during the drug development process. Recent advancements in artificial intelligence (AI), particularly in machine learning (ML) and deep learning (DL) techniques, have introduced innovative approaches to metabolism research, enabling more accurate predictions and insights. This paper emphasizes computational and AI-driven methodologies, highlighting how ML enhances predictive modeling for human metabolism at the molecular level and facilitates integration into genome-scale metabolic models at the omics level. Challenges remain such as data heterogeneity and model interpretability. This work aims to provide valuable insights and references for researchers in drug discovery and development, ultimately contributing to the advancement of precision medicine.
Drug delivery system of curcumin to the lungs based on poly(3-alloxyloxy-1,2-propylene succinate)-sebacic acid copolymers
Karolina Knap, Konrad Kwiecień, Jonasz Czajkowski, Rafał Szostecki, Daria Niewolik, Katarzyna Jaszcz, Peter Olinga, Katarzyna Reczyńska-Kolman, Elżbieta Pamuła
, Available online  , doi: 10.1016/j.jpha.2025.101434
Abstract(26) HTML Full Text PDF(2)
Abstract:
Polyanhydrides are attractive materials for drug delivery matrices as a result of their cytocompatibility and fast degradation rate. Here, we synthesized and characterized copolymers of poly(3-allyloxy-1,2-propylene succinate) (PSAGE) and sebacic acid (SBA). The successful polymerization was confirmed by proton nuclear magnetic resonance (1H NMR) and Fourier transform infrared (FTIR) spectroscopy analyses. The material with 40% PSAGE (PSAGE-SBA60) was more hydrophilic than the material with 20% PSAGE (PSAGE-SBA80) (water contact angle 82.2 ± 11.6° vs. 98.6 ± 8.9°, respectively). PSAGE-SBA60 also had a lower molecular weight than PSAGE-SBA80 (Mn = 6,400 Da vs. 9,800 Da). Both polyanhydrides were used to encapsulate curcumin (CUR) as a potential anti-inflammatory, antimicrobial and anticancer agent. The unloaded microparticles (MPs) and CUR-loaded MPs were produced using the emulsification/solvent evaporation method. The CUR was uniformly distributed within the MPs, as confirmed by fluorescence microscopy. All MPs had a geometric diameter < 5 μm and their surface charge was negative. MPs_PSAGE-SBA80 + CUR had the best aerodynamic properties, as shown by laser diffraction measurements and flowability parameters, i.e. Carr index and Hausner ratio. The MPs obtained from PSAGE-SBA60 degraded faster than those of PSAGE-SBA80. All MPs were noncytotoxic at a concentration of up to 100 μg/ml in the in vitro model (BEAS-2B lung epithelial cells) and ex vivo precision-cut tissue slices (PCTSs) rat model. The developed MPs are promising CUR carriers for pulmonary delivery in a dry powder formulation.
Legacy effects of lifestyle intervention on circulating metabolites in people with impaired glucose tolerance: a cross-sectional analysis of the Da Qing Diabetes Prevention Study
Meng Yu, Xin Qian, Hongmei Jia, Jinping Wang, Siyao He, Xinxing Feng, Yali An, Qiuhong Gong, Hongzhao You, Guangwei Li, Yanyan Chen, Zhongmei Zou
, Available online  , doi: 10.1016/j.jpha.2025.101433
Abstract(31) HTML Full Text PDF(7)
Abstract:
Lifestyle intervention is considered a global consensus for preventing and delaying the development of type 2 diabetes (T2D). This study aims to investigate the differences in metabolites associated with the long-term effect of lifestyle intervention in people with impaired glucose tolerance (IGT). The study enrolled 60 and 57 people with IGT who were originally assigned to the intervention and control (non-intervention) groups in a lifestyle intervention 6-year trial (1986-1992), respectively, as part of the Da Qing Diabetes Prevention Study. In 2006, 14 years after completion of the intervention trial, blood samples were collected for metabolomics analyses and T2D outcomes were assessed. Metabolomics outcomes were not analyzed at baseline. The untargeted metabolomics revealed that 14 plasma metabolites were significantly different between lifestyle intervention and control groups. Targeted metabolomics revealed that plasma concentrations of LysoPC(18:0/0:0) and SM(d18:1/16:1(9Z)) were significantly higher in the lifestyle intervention group compared with the control (16.72 ± 4.75 vs. 1.34 ± 0.40 and 2.60 ± 1.24 vs. 0.40 ± 0.08, P < 0.0001). A 1 μg/mL increase in LysoPC (18:0/0:0) and SM(d18:1/16:1(9Z)) was significantly associated with decreased risk of T2D (odds ratios were 0.82 (95% CI 0.75–0.90) and 0.17 (95% CI 0.07–0.39)) in all participants after adjusting for clinical confounders. In this cross-sectional study, the plasma LysoPC(18:0/0:0) and SM(d18:1/16:1(9Z)) differ between IGT people assigned to intervention and control groups 14 years after the 6-year intervention trial, suggesting they may have been related to the long-term legacy effects of these interventions.
A promising leap in early screening for chronic kidney disease: The smartphone-integrated handheld automated biochemical analyzer
Ming Chen
, Available online  , doi: 10.1016/j.jpha.2025.101436
Abstract(19) HTML Full Text PDF(2)
Abstract:
Non-targeted and chiral amino acid metabolomics of colon cancer: Revealing novel chiral biomarkers and metabolic pathways
Yuxuan Li, Xinxin Kong, Guangyi Zhang, Hongzhu Jin, Xi-Ling Li, Toufeng Jin, Jun Zhe Min
, Available online  , doi: 10.1016/j.jpha.2025.101429
Abstract(22) HTML Full Text PDF(1)
Abstract:
Menaquinone-7 alleviates mitochondrial dysfunction and senescence in senile osteoporosis by targeting the PINK1-mediated mitophagy via PXR/ERK/CREB signaling pathway
Yu Xu, Wencan Zhang, Wenpeng Xu, Shangzhi Li, Dingxin Zhang, Xiangyu Lin, Jincheng Liu, Qingyang Fu, Peijie H, Haipeng Si
, Available online  , doi: 10.1016/j.jpha.2025.101432
Abstract(52) HTML Full Text PDF(12)
Abstract:
Current therapeutic strategies for senile osteoporosis inadequately address its low-turnover pathology driven by mitochondrial dysfunction and cellular senescence. This study identifies menaquinone-7 (MK-7), a vitamin K2 isoform, as a novel therapeutic agent targeting mitochondrial homeostasis in senile osteoporosis. Through RNA sequencing analysis and intramedullary adeno-associated virus (AAV)-based gene manipulation in aged mice, cellular communication network factor 2 (Ccn2) was identified as a critical mediator of MK-7’s bone-protective effects. Biochemical and proteomic assays revealed that MK-7 binds to the nuclear receptor pregnane X receptor (PXR), activating the extracellular signal-regulated kinases 1/2 (ERK1/2)/cyclic AMP-responsive element-binding protein (CREB) signaling cascade to upregulate Ccn2 in senescent bone marrow mesenchymal stem cells (BMSCs). This pathway enhanced PTEN-induced kinase 1 (PINK1)/Parkin-mediated mitophagy, reducing mitochondrial DNA damage, reactive oxygen species (mtROS), and senescence-associated secretory phenotype (SASP), while restoring metabolic function. MK-7 redirected BMSC differentiation from adipogenic to osteogenic lineages, effectively mitigating age-related bone loss in vivo. Mechanistically, MK-7 stabilized PXR via direct interaction at the F285 residue, as confirmed by drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), and molecular docking. PXR activation further promoted ERK1/2/CREB-dependent Ccn2 expression, which orchestrated mitochondrial quality control and cellular energy metabolism. Our findings establish MK-7 as a dual-function agent that concurrently alleviates senescence and metabolic imbalance in bone tissue, offering a safe and targeted strategy for senile osteoporosis. This study provides critical insights into the pharmacological modulation of mitochondrial pathways and highlights MK-7’s translational potential in geriatric bone health.
Angelicin: A promising tricyclic aromatic agent for ulcerative colitis through cysteine-mediated proliferation of intestinal epithelial cells
Haifan LIU, Dunfang WANG, Lin ZHU, Tao LI, Bin LIU, Jingwei SUN, Xingbo ZUO, Siyuan CHEN, Jianyao LIU, Junying XIAN, Xue FENG, Caijuan ZHANG, Weipeng YANG
, Available online  , doi: 10.1016/j.jpha.2025.101435
Abstract(42) HTML Full Text PDF(4)
Abstract:
Angelicin (Ang), a natural tricyclic aromatic compound and quality marker derived from Fructus Psoraleae, exhibits significant anti-inflammatory efficacy. Fructus Psoraleae has long been utilized clinically for treating ulcerative colitis (UC). However, the specific role of Ang in UC remains poorly characterized. The present study aimed to elucidate the anti-UC effects of Ang and its underlying mechanisms. The anti-UC activity of Ang was evaluated using two UC models induced by dextran sulfate sodium (DSS) and 2,4,6-trinitrobenzenesulfonic acid (TNBS). Results demonstrated that Ang markedly inhibited the progression of UC. Microbial profiling indicated that the Ang-treated microbiome, particularly Lactobacillus murinus, provided protective effects against UC. Mechanistically, Ang facilitated proliferation of normal colonic epithelial cells, thus enhancing the intestinal mucosal barrier (IMB). Cysteine (Cys) played a crucial intermediary role by promoting glutathione (GSH) synthesis, maintaining redox homeostasis, and consequently facilitating cell proliferation. Additionally, increased Cys levels supported ribosomal biogenesis, enhancing protein translation and further stimulating cell proliferation. G-rich RNA sequence-binding factor 1 (GRSF1) was identified as a direct molecular target of Ang during ribosomal biogenesis. These findings indicated that Ang is a promising agent for promoting Cys-mediated cell proliferation, highlighting its role in maintaining redox homeostasis and protein translation. This study provides evidence supporting the future development of Ang as a therapeutic candidate for UC.
Distinct types of regulated cell death in atherosclerosis
Danyi Cao, Han Han, Deyong Yue, Guojun Shi, Yun Chen, Jiahai Shi, Guoliang Meng
, Available online  , doi: 10.1016/j.jpha.2025.101431
Abstract(36) HTML Full Text PDF(6)
Abstract:
Atherosclerosis is a chronic inflammatory disorder with high morbidity and mortality, leading to serious complications like myocardial infarction and strokes. Key cell types involved in atherosclerotic lesions include vascular endothelial cells (VEC), vascular smooth muscle cells (VSMC) and macrophages. Types of regulated cell death (RCD) are significant in the development and progression of atherosclerosis, including apoptosis, autophagy, necroptosis, efferocytosis, ferroptosis, pyroptosis, parthanatos, cuproptosis, lysosome-dependent cell death, NETotic cell death, paraptosis, alkaliptosis, oxeiptosis, entotic cell death and PANoptosis. The regulatory mechanisms and the crosstalk between different types of cells during atherosclerosis are complex, and the exact molecular basis remains obscure. Currently, numerous drugs and compounds have been found to attenuate atherosclerosis by targeting RCD. The review aims to provide an overview of RCD types related to VEC, VSMC, and macrophages in atherosclerosis, providing a reliable theoretical basis of the cellular mechanisms and exploring potential therapeutic strategies.
Small molecules targeting regulated cell death for chronic kidney disease therapy
Wen-Kai Yu, Qing-Ru Zhu, Li Zhou, Xin-Lei Shen, Tian-Yang Cheng, Yi-Ni Bao, Gang Cao
, Available online  , doi: 10.1016/j.jpha.2025.101427
Abstract(21) HTML Full Text PDF(2)
Abstract:

Chronic kidney disease (CKD) is a significant contributor to the global morbidity of non-communicable diseases and is predicted to become the fifth leading cause of death worldwide. However, effective treatments that directly target the underlying causes of CKD remain limited due to its complicated pathogenesis. Recent research has increasingly focused on elucidating the molecular mechanisms and identifying new therapeutic targets of CKD. In recent years, regulated cell death (RCD) has been highlighted as a central mechanism in the development and progression of CKD, suggesting that targeting specific RCD signaling pathways may offer effective strategies for CKD. Emerging research reveals that small molecules can effectively target different types of RCD in the context of CKD, including apoptosis, autophagy-dependent cell death, pyroptosis, ferroptosis and necroptosis. In this review, we summarize current understanding of the mechanism of RCD in CKD. Importantly, we emphasize the regulatory mechanism of small molecules on disturbed RCD to alleviate CKD. Taken together, this review enhances the comprehension of small molecules as modulators of RCD against CKD, which will provide new insights and potential avenues for CKD therapy.
Crebanine protects against ovariectomy-induced bone loss by targeting Sirt1 to interfere with NF-κB acetylation and ROS activity
Haojie Zhang, Xuan Zhao, Zheng Wang, Jiansen Miao, Xinli Hu, Peng Cui, Chen Jin, Xibin Zhao, Haibo Liang, Hantao Ye, Yining Xu, Xiaolong Chen, Wei Wang, Shibao Lu
, Available online  , doi: 10.1016/j.jpha.2025.101426
Abstract(77) HTML Full Text PDF(13)
Abstract:
Osteoporosis, the most prevalent skeletal disorder, is primarily driven by aberrantly increased osteoclast formation and/or activity. Targeting hyperactive osteoclasts remains the cornerstone of current therapeutic strategies. Crebanine (Cre), a natural isoquinoline-derived alkaloid with diverse pharmacological activities, has not yet been explored for osteoporosis treatment. This study aimed to evaluate the therapeutic potential of Cre against ovariectomy (OVX)-induced osteoporosis and elucidate its underlying mechanisms. Cre dose-dependently inhibited in vitro osteoclast differentiation, actin ring formation, and bone resorption by downregulating nuclear factor of activated T cells 1 (NFATc1) and key osteoclast-related genes. Simultaneously, Cre enhanced osteoblast differentiation and mineralization, upregulated osteoblast marker genes, and restored hydrogen peroxide-impaired alkaline phosphatase (ALP) activity impaired by hydrogen peroxide, indicating dual regulation of bone remodeling. Mechanistically, Cre activated sirtuin 1 (Sirt1), promoting p65 deacetylation, inactivated IκB kinase (IKK), and stabilized IκBα, thus inhibiting nuclear factor-kappaB (NF-κB) signaling. Additionally, Cre reduced reactive oxygen species (ROS) by upregulating antioxidant enzymes (heme oxygenase-1 (HO-1), catalase) and suppressing nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOX1/4). Furthermore, Cre specifically bound to the predicted site of receptor activator of NF-κB (RANK), blocking RANK ligand (RANKL)-RANK interaction and disrupting downstream protein kinase B (Akt) and mitogen-activated protein kinase (MAPK) signaling pathways. In the OVX mouse model, Cre significantly attenuated bone loss and osteoclastogenesis. Crucially, Cre showed no toxicity in liver or kidney function tests. Collectively, these findings demonstrate that Cre exerts dual therapeutic effects, inhibiting osteoclastogenesis via Sirt1-mediated NF-κB/ROS suppression and promoting osteoblast activity, providing a promising therapeutic strategy for osteoporosis.
Real-Time Visualization of Drug-Target Interactions in Native Subcellular Microenvironments for Lysosome-targeted Drug Discovery
Ran Wang, Yatong Yuan, Huarong Shao, Yuehao Sun, Changcheng Lai, Mengrui Zhang, Wenjing Song, Tao Zhang, Fengfeng Zhuang, Qixin Chen, Peixue Ling, Xintian Shao
, Available online  , doi: 10.1016/j.jpha.2025.101428
Abstract(34) HTML Full Text PDF(2)
Abstract:
Conventional ex vivo drug screening platforms struggle to recapitulate native subcellular microenvironments, leading to high off-target rates and compromised discovery of bioactive compounds. To address this, we developed subcellular target- tracking fluorescent-visualization-based interaction screening (SubTrack-FVIS), a platform combining super-resolution imaging with target-specific fluorescent tagging. SubTrack-FVIS first maps nanoscale spatial distributions of drug targets within living cells, then screens compound libraries to identify molecules specifically binding to target-enriched domains, and finally quantifies drug-target interactions through super- resolution imaging tracking. Compared to traditional toolbox, SubTrack-FVIS reduces off-target effects by evaluating compound binding within native subcellular architectures. When applied to the lysosomal vacuolar H+-ATPases (V-ATPase) subunit, ATP6V1A, a validated anti-cancer target, this approach identified for lysosomal alkalization fluorescent drug (LAFD) as a potent inhibitor. Super-resolution imaging revealed LAFD's dynamic binding to ATP6V1A clusters, enabling real-time visualization of V-ATPase inhibition and subsequent lysosomal destabilization. Crucially, SubTrack-FVIS uncovered LAFD's unique mechanism of blocking autophagosome-lysosome fusion, resolving autophagic flux obstruction at sub-100 nm resolution. This platform establishes a visualization framework for discovering drugs within physiological subcellular contexts while simultaneously decoding their mechanistic impacts, offering application potential for target-centric drug development.
A comprehensive review on herbal approaches for treatment of urinary tract infections: Scope and challenges
Md Saddam, Sujeet K. Mishra, Neelam Singh, Shyam Baboo Prasad, Smriti Tandon, Hemant Rawat, Ganesh Dane, Vijay Kumar, Ajay Kumar Meena, Ravindra Singh, Arjun Singh, Ch V. Narasimhaji, Narayanam Srikanth, Rabinarayan Acharya
, Available online  , doi: 10.1016/j.jpha.2025.101414
Abstract(33) HTML Full Text PDF(6)
Abstract:
Urinary tract infections (UTIs) have become a major health concern globally, necessitating effective treatments for mitigating discomfort and avert complications. The uropathogens commonly associated with UTIs in humans such as Bacillus species, Staphylococcus aureus (S. aureus), Pseudomonas aeruginosa (P. aeruginosa), and Escherichia coli (E. coli) are progressively developing resistance to current treatments and medications. The ancient wisdom of Ayurvedic medicines and its holistic approach can contribute to UTI treatment due to its lower toxicity, effectiveness against pathogens, and cost efficiency making it a viable option to complement or replace conventional treatments. This review delineates the key probable interactions between the bioactive components of antibacterial herbal drugs and UTI pathogens. Herbal drugs are rich in antioxidants such as flavonoids and polyphenols which can effectively neutralize free radicals and inhibit the formation of bacterial biofilms. These actions help alleviate oxidative stress and contribute to their anti-inflammatory effects. Certain specific herbs traditionally identified for their anti-inflammatory and antibacterial activity have been evaluated for their efficacy towards treatment of UTIs. Finally, the review addresses the challenges associated with herbal treatments of UTIs including issues related to standardization, dosage, and potential interactions with conventional medications that need to be overcome for broader acceptance and application.
An ultrasensitive and rapid immunoassay for the analysis of Helicobacter pylori in clinical samples based on hollow gold nanoparticles
Xiaorong Dai, Qingjie Zhang, Xianghui Yun, Yujuan Mao, Chuanjiang Ran, Zihan Ling, Yan Shen, Yongkang Chen, Liang Ge
, Available online  , doi: 10.1016/j.jpha.2025.101425
Abstract(24) HTML Full Text PDF(2)
Abstract:
Antibody screening for tumor and immune hotspot targets: the frontier of new methods and technologies
Yaping Zhou, Yitan Zou, Shaodong Lv, Dan Tan, Guangyao Li, Wenyan Fu, Changhai Lei, Mingdong Lu, Shi Hu
, Available online  , doi: 10.1016/j.jpha.2025.101417
Abstract(39) HTML Full Text PDF(3)
Abstract:
Advancements in tumor immunotherapy highlight the significant potential of antibody drugs, a key category of biological agents, for treating cancer and autoimmune diseases. This paper begins by defining and classifying key targets in tumor immunity, as well as discussing their structural and functional characteristics. Subsequently, it elaborates on innovative technologies for antibody drug screening, which, when integrated with contemporary molecular biology, biotechnology, and computational biology, have substantially enhanced the efficiency and accuracy of target identification and antibody drug screening processes. Despite the promising prospects of tumor immunotherapy, certain limitations persist in its practical implementation. In conclusion, this paper offers a comprehensive examination of the cutting-edge developments in tumor immunotherapy, focusing on the aspects of tumor immunotherapy itself, critical targets for immunotherapy, and novel technologies and methodologies for antibody screening. This analysis is crucial for advancing the field of tumor immunotherapy and for enhancing both therapeutic efficacy and safety. Furthermore, research and development of antibody drugs in other domains, such as autoimmune and inflammatory diseases, can benefit from it.
Beyond conventional therapies: Gut microbiota modulation and macromolecular drugs in the battle against cardiometabolic diseases
Jingyue Wang, Jing Qu, Mengliang Ye, Ru Feng, Xiang Hui, Xinyu Yang, Jingyu Jin, Qian Tong, Xianfeng Zhang, Yan Wang
, Available online  , doi: 10.1016/j.jpha.2025.101416
Abstract(36) HTML Full Text PDF(1)
Abstract:
Cardiometabolic diseases (CMDs) represent an ongoing major global health challenge, driven by complex interactions among genetic, environmental, and microbiome-related factors. While small-molecule drugs and lifestyle interventions can provide partial clinical benefits, they are possible to be constrained by the limited druggability of key target proteins, the potential for off-target effects, and difficulties in maintaining long-term adherence. In recent years, gut microbiota modulation and macromolecular drugs have emerged as promising therapeutic strategies. Gut microbiota modulation (e.g., probiotics, synbiotics, or natural products) exerts systemic metabolic and immune effects, supporting a therapeutic approach targeting multiple diseases. Meanwhile, macromolecular drugs (e.g., peptides, antibodies, and small nucleic acids) offer precise, pathway-targeted interventions. Despite advancements, limitations remain in addressing ethical considerations in microbiota modulation and optimizing targeted delivery systems, all of which may hinder clinical translation. Here, we provide a comprehensive overview of therapeutic approaches for CMDs, with a focus on obesity, type 2 diabetes mellitus (T2DM), and atherosclerosis (AS). The review is structured around three key aspects: 1) conventional therapies, including small-molecule drugs and lifestyle interventions; 2) emerging therapies, encompassing gut microbiota modulation, macromolecular drugs and their interactions; and 3) challenges and opportunities for comorbidity management, microbiota ethics and artificial intelligence (AI)-driven therapeutic optimization. We hope this review enhances the understanding of small-molecule drugs, lifestyles interventions, gut microbiota modulation and macromolecular drugs in the management of CMDs, thereby fostering medical innovation and contributing to the development of system-based comprehensive therapeutic paradigms.
Targeted nano-drug delivery systems for tumor immunotherapy
Shan Lian, Wenyong Yang, Yan Zeng, Ranran Tang, Kui Wang
, Available online  , doi: 10.1016/j.jpha.2025.101408
Abstract(28) HTML Full Text PDF(3)
Abstract:
While being a safe and effective precision therapy strategy, tumor immunotherapy still fails in many patients due to immunosuppressive microenvironment. Emerging evidence has indicated that the targeted nano-drug delivery systems can accurately deliver therapeutic agents to potentiate the efficacy of immunotherapy. This review will outline recent advances in applying targeted nano-drug delivery systems in immunotherapy, with an emphasis on their crucial roles in regulating innate immunity response, adaptive immunity response, and immunogenic cell death. We will also discuss the current challenges and future opportunities for the clinical translation of targeted nano-drug delivery systems for tumor immunotherapy.
Rational design of a novel specific fluorescent substrate for monitoring hUGT1A4 activity and its application in identification of selective inhibitors
Ning Mao, Shi-Qing Li, Xiang-Lu Zhou, Cong Hu, Wen-Chao Wu, Hua Wei, Li-Wei Zou, Ling Yang
, Available online  , doi: 10.1016/j.jpha.2025.101415
Abstract(37) HTML Full Text PDF(3)
Abstract:
Uridine diphosphate (UDP)-glucuronosyltransferases (UGTs) are a family of enzymes with highly similar amino acid sequences, making it challenging to distinguish between their roles. Developing selective probes and inhibitors is essential for understanding the unique functions of each isoform. In this study, we synthesized four novel naphthalimide-based fluorescent probes bearing nitrogen-containing substituents at the 4-position and identified N-(n-butyl)-4-(4-methylpiperazin-1-yl)-1,8-naphthalimide (BAD3) as a highly selective and sensitive substrate for UDP glucuronosyltransferase 1A4 (UGT1A4). Using BAD3, we established an inhibitor screening platform and identified ursolic acid (T7) as a promising lead compound from a natural product library. Structure-activity relationship (SAR) studies revealed that esterification at the 3-hydroxyl group significantly enhanced inhibitory activity, yielding two potent inhibitors, T25 and T26, while modifications at the 28-carboxyl group reduced activity. Further characterization confirmed T25 (inhibition constant (Ki) = 0.64 μM) and T26 (Ki = 0.61 μM) as selective and competitive UGT1A4 inhibitors. Molecular docking revealed that the 28-carboxyl group plays a crucial role by forming a salt bridge with Arg258 in the UGT1A4 active site. In vivo studies demonstrated that T25 significantly altered the pharmacokinetic profile of BAD3, confirming its inhibitory effect on UGT1A4 in animals. Together, BAD3 and the selective inhibitors T25/T26 serve as valuable molecular tools for studying the physiological and pharmacological roles of UGT1A4.
Unlocking Wnt’s Weak Spot: Glycosylated Nanoalbumins to Reignite Immune Responses in MSS-CRC
Xin Wei, Mingzhu Zuo, Qiongwen Liang, Shiwei Zhang, Jingmei Wang, Zhanfeng Li, Wenguang Yang, Fang Ma, Wangxiao He, Tianya Liu
, Available online  , doi: 10.1016/j.jpha.2025.101412
Abstract(23) HTML Full Text PDF(0)
Abstract:
Microsatellite-stable colorectal cancer (MSS-CRC) is characterized by poor immune infiltration and immune evasion, leading to rapid tumor progression and limited efficacy of current immunotherapies. The bioinformatics analysis revealed that the hyperactivation of the Wnt/β-catenin signaling pathway in MSS-CRC is instrumental in mediating immune suppression. Although inhibiting this pathway presents a therapeutic opportunity, no Wnt inhibitors have been clinically approved due to Wnt's essential role in maintaining tissue homeostasis, with inhibition in normal cells causing significant toxicity. To address it, we discovered that Wnt activation in colorectal cancer cells enhances macropinocytosis, particularly favoring the uptake of glycosylated proteins to meet increased nutrient demands. Building on this insight, we developed a glycosylated human serum albumin (GHSA) co-assembled with carnosic acid (CA), termed glycosylated human serum albumin-carnosic acid (GHSACA), which is selectively internalized by Wnt-activated colorectal cancer cells. This approach not only reduces off-target toxicity but also effectively inhibits the Wnt pathway, resulting in notable tumor inhibition and immune reactivation in murine models, while maintaining a favorable safety profile. This strategy offers a promising therapeutic solution by combining selective Wnt inhibition with enhanced immune activation in MSS-CRC, and highlights the potential of leveraging disease-specific cellular uptake mechanisms for designing nanomedicines, advancing the development of precision-targeted cancer therapies.
Therapeutic strategies based on macrophages and their derivatives: Targeted drug delivery platforms and disease treatment
Jiali Fu, Shiyun Huang, Anqi Zhang, Rongying Shi, Yuhao Wei, Shanshan He, Shiqi Huang, Lin Li, Xun Sun, Tao Gong, Ling Zhang, Qing Lin, Zhirong Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101413
Abstract(39) HTML Full Text PDF(0)
Abstract:
Targeted drug delivery platforms are designed to enable spatiotemporal precision in transporting therapeutic agents to disease-specific sites, thereby optimizing therapeutic efficacy and mitigating off-target adverse effects. Despite their clinical promise, these platforms remain hindered by substantial translational barriers. Macrophages, with inherent biocompatibility and intrinsic tropism toward inflamed/diseased tissues, are critically involved in diverse pathological processes. Macrophage-based drug delivery systems (MDDSs) have emerged as promising platforms engineered via therapeutic cargo loading onto intact cells, cell-membrane coatings; extracellular vesicles (EVs), or hitchhiking mechanisms. This review delineates existing MDDS platforms, critically analyzing their respective merits and constraints. We further elucidate therapeutic mechanisms and clinical implementations of MDDSs for cancer, atherosclerosis (AS), and central nervous system (CNS) disorders, while establishing a systematic taxonomy of their biomedical applications. Specifically, we highlight the transformative potential of gene-editing technologies (exemplified by chimeric antigen receptor macrophage (CAR-M) therapy and antigen-independent strategies) in innovating next-generation MDDS architectures. We summarize state-of-the-art developments, persisting translational hurdles, and optimization roadmaps for MDDSs, providing a conceptual framework to guide their translational advancement.
Gliquidone alleviates DSS-induced ulcerative colitis in rats by targeting carnitine palmitoyltransferase 1A
Tian Tang, Ying Zhang, Xinrui Xing, Ruiqi Sun, Zhe Yu, Yuan Tian, Zunjian Zhang, Pei Zhang, Fengguo Xu
, Available online  , doi: 10.1016/j.jpha.2025.101409
Abstract(31) HTML Full Text PDF(6)
Abstract:
Ulcerative colitis (UC) is an idiopathic, chronic inflammatory disorder with an increasing incidence worldwide. Due to the complex and unclear therapeutic targets, unmet UC therapeutic drugs still exist. Recently, acylcarnitine metabolism disorder has been linked to intestinal inflammation, but its role in UC remains elusive. According to our preliminary non-targeted metabolomics data, acylcarnitines (ACs) was screened as the disturbed metabolites in the different intestinal inflammation-related diseases. Here we quantified 26 ACs within liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the dextran sulfate sodium (DSS)-induced UC rat model, and found that long-chain acylcarnitines (LCACs) were increased to varying degrees. As the key metabolites of fatty acid β-oxidation (FAO), the upstream metabolites long-chain fatty acids (LCFAs) and the related metabolic enzymes were further characterized, the results showed that the rate-limiting enzyme carnitine palmitoyltransferase 1A (CPT1A)-mediated LCFAs-LCACs metabolic axis was activated sharply. Next in vitro experiments exhibited that CPT1A was significantly upregulated in both inflammatory macrophages and colonic epithelial cells, and inhibition or knockdown of CPT1A could reduce the inflammation level remarkably. Thus, we screened the pharmacologic inhibitors of CPT1A from FDA approved drugs, within molecular docking, Western blot and cell membrane chromatography (CMC) technology, gliquidone was found to inhibit CPT1A in a dose-dependent manner and exert anti-inflammatory effects in vitro. Animal experiments also showed that gliquidone alleviated DSS-induced UC significantly. In summary, our study presents that within metabolomics analysis, inhibiting CPT1A is focused to be a potential therapeutic strategy against UC, and gliquidone represents an alternative treatment.
A comprehensive review of Intelligent Question-Answering Systems in Traditional Chinese Medicine Based on LLMs
Qilan Xu, Tong Wu, Yiwen Wang, Xingyu Li, Heshui Yu, Shixin Cen, Zheng Li
, Available online  , doi: 10.1016/j.jpha.2025.101406
Abstract(16) HTML Full Text PDF(8)
Abstract:
Large language models (LLMs) are advanced deep learning models with billions or even trillions of parameters, enabling powerful natural language processing and knowledge reasoning capabilities. Their applications in the medical domain have been rapidly expanding, spanning medical research, clinical diagnosis, drug development, and patient management. As a cornerstone of China's healthcare system, traditional Chinese medicine (TCM) faces significant challenges, including difficulties in knowledge extraction, and lack of standardization. The emergence of TCM-focused LLMs presents a transformative opportunity, offering a novel technological framework to process vast amounts of TCM data, uncover hidden theoretical insights, and enhance both research and clinical applications. Despite the growing interest in AI-driven medical solutions, systematic research on LLMs in the TCM domain remains limited. This article provides a comprehensive review of LLM development, detailing their underlying mechanisms, training methodologies, and key technological advancements. It further explores the unique characteristics and diverse application scenarios of existing TCM-LLMs. Additionally, this study also conducts a horizontal comparison of the differences between intelligent question-answering (QA) systems on general LLMs and QA systems on TCM-LLMs, discusses challenges and potential risks, and offers strategic recommendations for future development. By synthesizing current advancements and addressing critical gaps, this work aims to support the continued modernization and intelligent evolution of TCM, fostering its integration into contemporary healthcare systems.
Studies and Analysis of Drug-Target Interactions by Affinity Chromatography and Related Techniques: A Review
David S. Hage, Sadia Sharmeen, B.K. Sajeeb, Harshana Olupathage, Md Masudur Rahman, Isaac Kyei, Samiul Alim, Nigar Sultana Pinky
, Available online  , doi: 10.1016/j.jpha.2025.101407
Abstract(4) HTML Full Text PDF(0)
Abstract:
The characterization of drug-target interactions is a key component of drug discovery, testing, and development. Affinity chromatography is one approach that can be used for this type of analysis. For instance, this may be done by using an immobilized target as a stationary phase and a drug as the applied solute. This review will discuss the various ways in which affinity chromatographic methods have been used to examine drug-target interactions, with an emphasis on high-performance methods. The general principles of this approach and factors to consider in its use for drug-target interaction analysis will first be examined. Methods based on zonal elution or frontal analysis for binding and competition studies will then be discussed. Various techniques for kinetic studies will next be considered, along with approaches that employ secondary binding agents and hybrid techniques. In each case, the general principles and theory of an approach will be given along with examples of its use in drug-target interaction studies. Advantages or limitations of each approach will be provided as well. This information should make it possible in the future to extend these techniques to other drug-target systems of interest in biomedical research and drug testing or development.
Unveiling optimal molecular features for hERG insights with automatic machine learning
Congying Xu, Youjun Xu, Ziang Hu, Xinyi Zhao, Weixin Xie, Weiren Chen, Jianfeng Pei
, Available online  , doi: 10.1016/j.jpha.2025.101411
Abstract(38) HTML Full Text PDF(1)
Abstract:
We developed MaxQsaring, a novel universal framework integrating molecular descriptors, fingerprints, and deep-learning pretrained representations, to predict the properties of compounds. Applied to a case study of human ether-à-go-go-related gene (hERG) blockage prediction, MaxQsaring achieved state-of-the-art performance on two challenging external datasets through automatic optimal feature combinations, and successfully identified top the 10 important interpretable features that could be used to model a high-accuracy decision tree. The models’ predictions align well with empirical hERG optimization strategies, demonstrating their interpretability for practical utilities. Deep learning pre-trained representations have been demonstrated to exert a moderate influence on enhancing the performance of predictive models. Nevertheless, their impact on augmenting the generalizability of these models, particularly when applied to compounds possessing novel scaffolds, appears to be comparatively minimal. MaxQsaring excelled in the Therapeutics Data Commons (TDC) benchmarks, ranking first in 19 out of 22 tasks, showcasing its potential for universal accurate compound property prediction to facilitate a high success rate of early drug discovery, which is still a formidable challenge.
HyPepTox-Fuse: An interpretable hybrid framework for accurate peptide toxicity prediction fusing protein language model-based embeddings with conventional descriptors
Duong Thanh Tran, Nhat Truong Pham, Nguyen Doan Hieu Nguyen, Leyi Wei, Balachandran Manavalan
, Available online  , doi: 10.1016/j.jpha.2025.101410
Abstract(35) HTML Full Text PDF(2)
Abstract:
Peptide-based therapeutics hold great promise for the treatment of various diseases; however, their clinical application is often hindered by toxicity challenges. The accurate prediction of peptide toxicity is crucial for designing safe peptide-based therapeutics. While traditional experimental approaches are time-consuming and expensive, computational methods have emerged as viable alternatives, including similarity-based and machine learning (ML)-/deep learning (DL)-based methods. However, existing methods often struggle with robustness and generalizability. To address these challenges, we propose HyPepTox-Fuse, a novel framework that fuses protein language model (PLM)- based embeddings with conventional descriptors. HyPepTox-Fuse integrates ensemble PLM-based embeddings to achieve richer peptide representations by leveraging a crossmodal multi-head attention mechanism and Transformer architecture. A robust feature ranking and selection pipeline further refines conventional descriptors, thus enhancing prediction performance. Our framework outperforms state-of-the-art methods in crossvalidation and independent evaluations, offering a scalable and reliable tool for peptide toxicity prediction. Moreover, we conducted a case study to validate the robustness and generalizability of HyPepTox-Fuse, highlighting its effectiveness in enhancing model performance. Furthermore, the HyPepTox-Fuse server is freely accessible at https://balalab-skku.org/HyPepTox-Fuse/ and the source code is publicly available at https://github.com/cbbl-skku-org/HyPepTox-Fuse/. The study thus presents an intuitive platform for predicting peptide toxicity and supports reproducibility through openly available datasets.
Apatinib and silver nanoparticles synergize against gastric cancer through the PI3K/Akt signaling pathway-mediated ferroptosis
Zichang Lin, Zhenghao Deng, Jiahao Liang, Binlong Chen, Yanyan Huang, Bin Liu, Yanzhong Zhao
, Available online  , doi: 10.1016/j.jpha.2025.101400
Abstract(85) HTML Full Text PDF(12)
Abstract:
Ferroptosis, a regulated form of cell death characterized by lipid peroxidation (LPO), has emerged as a promising target in cancer therapy. In this study, we detected elevated levels of glutathione (GSH) peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) in human gastric adenocarcinoma tissues, indicating a suppression of ferroptosis in gastric cancer (GC). Apatinib (Apa), a vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitor, was found to induce ferroptosis through the classical SLC7A11/GSH/GPX4 pathway. However, long-term administration of high-dose Apa is associated with adverse side effects and the risk of drug resistance. To address these limitations, we developed a novel drug delivery system using hyaluronic acid (HA)-modified poly (lactic-co-glycolic acid) (PLGA) nanoparticles for targeted co-delivery of Apa and chitosan-coated silver nanoparticles (Chi-Ag). Our results demonstrated that the combination of Apa and Chi-Ag exerted a synergistic cytotoxic effect against GC cells. This co-delivery system evidently increased oxidative stress at the tumor site and effectively promoted ferroptosis via modulation of the phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling pathway. In summary, we present a targeted nanoplatform that enhances the antitumor efficacy of Apa at lower dosages by leveraging ferroptosis induction. This strategy holds promise for improving the clinical outcomes in patients with GC.
Innovative perspective on the geographical origin and quality of Peucedanum praeruptorum Dunn through the integration of inorganic and organic substance profiles
Yaolei Li, Hao Wu, Jing Fan, Jinjian Huang, Hongyu Jin, Feng Wei
, Available online  , doi: 10.1016/j.jpha.2025.101405
Abstract(51) HTML Full Text PDF(5)
Abstract:
The clinical efficacy of traditional Chinese medicines (TCMs) is closely linked to their genuine quality. Identifying the geographical origin and genuine characteristics of medicinal materials is pivotal for enhancing quality control and efficacy. Qianhu (Peucedanum praeruptorum Dunn), a commonly used TCM, still lacks a clear understanding of the specific connection between its quality and geographical origin. To bridge this gap, we innovatively propose a new recognition model that integrates inorganic and organic substances, using Qianhu as the model TCM. By incorporating the concepts of metallomics and metabolomics, we merge elemental fingerprint profiles with chemical component contour maps to pinpoint its geographical origin. The research findings suggested that, compared to chemometrics, machine learning with data oversampling could precisely identify Qianhu from areas like Anhui, Zhejiang, Guizhou, and Chongqing of China, especially distinguishing genuine ones. Upon this groundwork, we further introduced an innovative ensemble model that deeply integrated the optimal models for elements and chemical components, thereby substantially enhancing classification accuracy. Additionally, through variable importance analysis, we provided professional and in-depth interpretations for the elements and chemical components within the model. In summary, this study, for the first time, revealed the scientific basis of Qianhu's producing area and genuine quality through machine learning, integrating inorganic and organic factors. It provides a solid foundation for scientific and reasonable quality control and clinical application of TCMs.
Intestinal anti-inflammatory drug targets as potential modifiers of cardiovascular disease risk
Shuangshuang Tong, Junjun Ye, Yanlin Lyu, Jiating Su, Baoxin Yan, Xianzhen Cai, Barkat Ali Khan, Muhammad Azhar Ud Din, Kaijian Hou, Jilin Li
, Available online  , doi: 10.1016/j.jpha.2025.101403
Abstract(81) HTML Full Text PDF(4)
Abstract:
Dual regulation of antiviral IFN response by Scutellariae Radix: Therapeutic implications for influenza
Li Li, Manjing Jiang, Hong Wei, Linpan Liang, Yunlong Song, Dongni Xia, Qiang Luo, Huimin Huang, Xu Li, Haisheng Yang, Lijun Ning, Ying Wu
, Available online  , doi: 10.1016/j.jpha.2025.101399
Abstract(58) HTML Full Text PDF(5)
Abstract:
Scutellariae Radix (SR) is widely used in Chinese medicine for influenza treatment; however, the mechanisms underlying its effect remain unknown. Here, we report, for the first time, that the therapeutic effects of SR on influenza involve regulation of antiviral interferons (IFNs), type I and type III IFNs (IFN-Is and IFN-IIIs, respectively), particularly through the modulation of IFN-I production and its downstream effects in a cell type-specific manner. SR treatment resulted in symptomatic improvement in A/Puerto Rico/8/34 (H1N1) virus (PR8)-infected mice. It exhibited direct antiviral activity in the early stages of virus infection in PR8/A/WSN/33 (H1N1) (WSN)-infected Madin-Darby canine kidney (MDCK) cells. Next, we investigated the effects of SR on the upstream antiviral IFN pathways and downstream effects in human lung adenocarcinoma (A549) cells, human monocytic leukemia (THP-1) cells, and neutrophils (Neu). SR exhibited dual regulatory roles, enhancing the production and activity of antiviral IFNs via the nuclear factor-kappaB (NF-κB)/IFN regulatory factor 3 (IRF3) and Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathways. It also reduced IFN-I-induced neutrophil inflammation by inhibiting reactive oxygen species and neutrophil extracellular trap production, and alleviated inflammation in A549 and THP-1 cells via NF-κB/cfos or mitogen-activated protein kinase (MAPK)/c-Jun signaling. Subsequently, the importance of IFN-I/IFN-III was verified using IFN alpha and beta receptor 1 (Ifnar1)-/- and IFN lambda receptor 1(Ifnlr1)-/- mice. The absence of IFNAR or IFNLR significantly diminished the therapeutic effect of SR against influenza, highlighting its dependence on the IFN-I/IFN-III systems. Finally, a delayed drug administration experiment in PR8-infected mice revealed that the therapeutic effect of SR heavily relies on early induction of IFN. Overall, our findings offer valuable insights for the clinical utilization of SR, as well as for further exploration of antiviral treatments.
Citric acid disassembles α-synuclein fibrils and reduces their cytotoxicity
Hyo Gi Jung, Yeon Ho Kim, Junho Bang, Dongsung Park, Jae Won Jang, Yonghwan Kim, Hyunji Kim, Kyo Seon Hwang, Jeong Hoon Lee, Dongtak Lee, Dae Sung Yoon
, Available online  , doi: 10.1016/j.jpha.2025.101404
Abstract(42) HTML Full Text PDF(2)
Abstract:
Establishment of an at-line nanofractionation-based screening platform for rapid identification of influenza PAN/PAN I38T inhibitors from Artemisiae Argyi
Yuexiang CHANG, Hao TIAN, Jia-Huan QU, Jiaming YUAN, Rongkai GU, TingTing ZHANG, Jincai WANG, Zhengjin JIANG
, Available online  , doi: 10.1016/j.jpha.2025.101402
Abstract(60) HTML Full Text PDF(5)
Abstract:
The N-terminal domain of influenza viral polymerase (PAN), a highly conserved region with critical catalytic function related to viral RNA replication and transcription, is considered as a very promising anti-influenza drug target. There is an urgent need for highly efficient and rapid screening methods to identify potential PAN inhibitors (PANIs) from complex matrices. In this work, a novel high-throughput screening (HTS) platform was established by coupling high performance liquid chromatography and high-resolution mass spectrometry (HPLC-HRMS) with a fluorescence resonance energy transfer (FRET)-based endonuclease activity assay through an at-line nanofractionation system (ANF). The proposed screening platform could rapidly identify potential PANIs from plant extracts with good sensitivity (baloxavir at the half maximal inhibitory concentration (IC50) could be detected) and reliability (Z’ factor of 0.77). This platform was then successfully applied to the screening of potential inhibitors against PAN/PAN I38T from an aqueous extract of Artemisiae Argyi and 17 potential PANIs were identified. Among them, three compounds (cynarine, isochlorogenic acid B and isochlorogenic acid C) showed comparable inhibitory activity against PAN and even better activity against PAN I38T compared to baloxavir. This study not only established a novel high-throughput ANF-based PANIs screening platform, but also proved the feasibility to discover PANIs from complex TCMs, which has a great potential in future anti-influenza drug discovery.
MST4 as a Key Driver of Osteoclast Activation in Osteoporosis
Bin Zhang, Jiangjiang Zhang, Xuqiang Liu, Qiang Xu
, Available online  , doi: 10.1016/j.jpha.2025.101401
Abstract(54) HTML Full Text PDF(1)
Abstract:
Osteoporosis, characterized by excessive bone resorption driven by heightened osteoclast activity, remains a major health concern with molecular mechanisms that are not fully understood. This study explores the role of mammalian Sterile 20-like kinase 4 (MST4), a member of the Sterile 20 (Ste20) kinase family, in osteoclast differentiation and function. Analysis of blood samples from osteoporosis patients revealed a significant increase in MST4 expression compared to healthy controls, with a negative correlation to bone mineral density (BMD). In vitro experiments using stem cell-derived osteoclast models showed that MST4 knockdown reduced osteoclast differentiation and bone resorption activity, whereas MST4 overexpression enhanced these processes. In vivo studies with ovariectomized (OVX) mouse models further corroborated these findings. Mechanistically, MST4 was found to promote tumor necrosis factor receptor-associated factor 6 (TRAF6) autoubiquitination through phosphorylation, a critical event for osteoclast activation. Collectively, these results identify MST4 as a key regulator of osteoclast-mediated bone resorption in osteoporosis, suggesting that targeting the MST4–TRAF6 signaling axis may offer a novel therapeutic strategy to prevent bone loss.
Profiling cytotoxicity of nanofractionated elapid snake venoms in human cell lines representing different tissues
Haifeng Xu, Mátyás A. Bittenbinder, Julien Slagboom, Nicholas R. Casewell, Paul Jennings, Jeroen Kool
, Available online  , doi: 10.1016/j.jpha.2025.101398
Abstract(46) HTML Full Text PDF(9)
Abstract:
Elapid snakebites cause severe toxicity, predominantly neurotoxicity and general cytotoxicity. However, the specific cellular impacts of individual venom toxins remain largely underexplored. This study developed a high-throughput platform for profiling cytotoxicity from elapid venoms, focusing on nanofractionation analytics to enhance selectivity and toxin identification. Elapid Venoms were tested on four human cell lines, representing kidney (RPTEC/TERT1), liver (HepaRG), endothelial (iPSC-EC), and skin (HaCaT) tissues. Cytotoxic effects were assessed through cell coverage, viability, and metabolic assays in both crude and nanofractionated venom samples. Nanofractionation revealed selective cytotoxicity in venom components, notably phospholipases A2 (PLA2s) and three-finger toxins (3FTxs), which impaired membrane integrity and cellular metabolism. Crude B. multicinctus venom displayed specific cytotoxicity toward liver and skin cells but not kidney or endothelial cells. Cytotoxicity of nanofractionated B. multicinctus venom was lost, likely due to denaturing conditions of the reversed-phase separation. Fractionation after size exclusion chromatography (SEC) for post-column bioassaying to avoid toxin denaturation yielded bioactive fractions, with 3FTxs, PLA2s, and Kunitz-type serine protease (KUNs) likely responsible for the observed cell permeability disruption, extracellular matrix (ECM) degradation, and metabolic loss. This integrated analytical workflow, combining nanofractionation with high-throughput cytotoxicity assays and venomics, enabled rapid identification of venom components with cell type-specific toxicity. Our findings contribute to understanding elapid venom toxicity and can aid in developing targeted snakebite treatments focusing on cytotoxicity responsible for tissue-specific damage.
Carbonyl content assay to monitor squalene-in-water vaccine adjuvant oxidation
Emory M. Payne, Erika Patel, Faith O. Osinaga, Marissa L. Wolfle, Tian Lu, Velabo Mdluli, Patricia M. Egan, William J. Smith
, Available online  , doi: 10.1016/j.jpha.2025.101397
Abstract(43) HTML Full Text PDF(3)
Abstract:
Development and validation of a static multiple light scattering (SMLS) method for real-time colloidal stability assessment in nanoparticle formulations
Haiyang Shen, Shiqi Huang, Renjie Li, Hongliang Wang, Yanfang Yang, Yuling Liu, Jun Ye, Xiaohai Ma
, Available online  , doi: 10.1016/j.jpha.2025.101396
Abstract(26) HTML Full Text PDF(2)
Abstract:
This study presents the first development and validation of a static multiple light scattering (SMLS)-based method for real-time, non-invasive assessment of nanoparticle colloidal stability. Nanoparticles, leveraging their nanoscale advantages (e.g., targeted delivery, enhanced drug solubility, and controlled release), hold transformative potential in treating diseases. However, their clinical success hinges on colloidal stability, which dictates in vivo behavior, safety, and regulatory compliance. While dynamic light scattering (DLS) remains widely used, its inability to monitor dynamic transformations and reliance on sample dilution limit its accuracy. Here, we pioneer the application of SMLS to systematically evaluate colloidal stability across standardized particles and commercial nanoparticle formulations (liposomes, nanoparticles, micelles, and nanoemulsions). Results demonstrate that SMLS captures destabilization kinetics (aggregation, sedimentation, creaming) in real-time without dilution, even at high concentrations, while DLS fails to distinguish polydisperse systems due to time-point sampling. The Turbiscan stability index (TSI) quantifies instability mechanisms, correlating with particle size distribution broadening. This first comprehensive validation of SMLS for nanoparticles reveals its superiority in reflecting native-state behavior, exemplified by minimal or the variations in the average transmission (ΔT) or backscattering intensity (ΔBS) fluctuations and low TSI values in four commercial formulations. By addressing a critical technological gap, this study establishes SMLS as an indispensable tool for optimizing nanoparticle design, ensuring compliance with U.S. Food and Drug Administration (FDA) in-use stability guidelines, and accelerating clinical translation.
Fast-Adapting Graph Neural Network with Prior Knowledge for Drug Response Prediction Across Preclinical and Clinical Data
Hui Guo, Xiang Lv, Shenghao Li, Daichuan Ma, Yizhou Li, Menglong Li
, Available online  , doi: 10.1016/j.jpha.2025.101386
Abstract(26) HTML Full Text PDF(1)
Abstract:
Efficient drug response prediction is crucial for reducing drug development costs and time, but current computational models struggle with limited experimental data and out-of-distribution issues between in vitro and in vivo settings. To address this, we introduced drug response prediction meta-learner (metaDRP), a novel few-shot learning model designed to enhance predictive accuracy with limited sample sizes across diverse drug-tissue tasks. metaDRP achieves performance comparable to state-of-the-art models in both genomics of drug sensitivity in cancer (GDSC) drug screening and in vivo datasets, while effectively mitigating out-of-distribution problems, making it reliable for translating findings from controlled environments to clinical applications. Additionally, metaDRP’s inherent interpretability offers reliable insights into drug mechanisms of action, such as elucidating the pathways and molecular targets of drugs like epothilone B and pemetrexed. This work provides a promising approach to overcoming data scarcity and out-of-distribution challenges in drug response prediction, while promoting the integration of few-shot learning in this field.
FPS_P/N: A two-dimensional mass spectrometry utilization program with precursor ion determination for accurately distinguishing anthocyanin from other flavonoids
Ya-Hui Ge, Lili Zhang, Shilin Gong, Wen Miao, Li Zhang, Weibin Bai, Jian-Lin Wu, Na Li
, Available online  , doi: 10.1016/j.jpha.2025.101385
Abstract(63) HTML Full Text PDF(2)
Abstract:
Anthocyanins, a unique class of flavonoids with flavylium skeletons, are valued for antioxidant properties. However, distinguishing anthocyanins from co-existing flavonoids using conventional automated tandem mass spectrometry (MS) analysis methods remains challenging. This difficulty arises from low specificity of MS features and confusion of precursor ions, leading to substantial false confidence annotations. To address it, we have developed the strategy of positive (POS)-to-negative (NEG) primary MS (MS1) intensity ratios detecting with fast polarity switching (FPS), termed FPS-POS/NEG, to determine their specific precursor ions. Moreover, we developed an automated program leveraging FPS-POS/NEG strategy (FPS_P/N) streamlining i) screening candidate pool with molecular networking analysis from MS1 and secondary MS (MS2), ii) determining precursor ions with FPS-POS/NEG, and iii) annotation with MS2. This program enables simultaneous capture of positive and negative signals in a single run and accurate determination of precursor ions for anthocyanins (5.98 to 9.28) and other flavonoids (-2.52 to 2.08). The underlying mechanisms were elucidated by difference in protonated and deprotonated Gibbs free energy and in-source fragmentation (ISF). FPS-POS/NEG strategy was validated across a broad pH range (0.1%-2% formic acid) and demonstrated high alignment accuracy (retention time difference, 0.011 min) and consistency (relative standard deviation (RSD), 0.38%-4.62%). Using blueberry, 20 anthocyanins (nonacylated and acylated) and 14 additional flavonoids were annotated. With two-dimensional integration of positive and negative MS1 intensities with intensity ratios, FPS_P/N program provides a novel way to identify anthocyanins from other flavonoids. We anticipate this innovative method will enhance the high-throughput qualification of anthocyanins and other flavonoids in complex samples.
ToxBERT: An explainable AI framework for enhancing prediction of adverse drug reactions and structural insights
Yujie He, Xiang Lv, Wuling Long, Shengqiu Zhai, Menglong Li, Zhining Wen
, Available online  , doi: 10.1016/j.jpha.2025.101387
Abstract(78) HTML Full Text PDF(2)
Abstract:
Accurate prediction of drug-induced adverse drug reactions (ADRs) is crucial for drug safety evaluation, as it directly impacts public health and safety. While various models have shown promising results in predicting ADRs, their accuracy still needs improvement. Additionally, many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints, which can introduce bias. To address these challenges, we propose ToxBERT, an efficient transformer encoder model that leverages attention and masking mechanisms for SMILES representations. Our results demonstrate that ToxBERT achieved area under the receiver operating characteristic curve (AUROC) scores of 0.839, 0.759, and 0.664 for predicting drug-induced QT prolongation, rhabdomyolysis, and liver injury, respectively, outperforming previous studies. Furthermore, ToxBERT can identify drug substructures that are closely associated with specific ADRs. These findings indicate that ToxBERT is not only a valuable tool for understanding the mechanisms underlying specific drug-induced ADRs but also for mitigating potential ADRs in the drug discovery pipeline.
Recent trends in mesoporous carbon-based nanoplatforms for biomedical application
Wei Yang, Jinnian Ge, Mohan Jiang, Nan Zhang, Qinghe Yang, Kaisheng Nan, Qinfu Zhao, Long Wan, Xiaofan Wang
, Available online  , doi: 10.1016/j.jpha.2025.101383
Abstract(51) HTML Full Text PDF(5)
Abstract:
Mesoporous carbon nanoparticles (MCNs) have received considerable attention for biomedical applications due to their unique structural features, including high specific surface area, adjustable pore size, and remarkable biocompatibility. These properties have addressed key challenges such as inefficiencies in drug loading and release, minimizing the side effects associated with conventional treatments. In this review, the classification and the research progress of MCNs are summarized firstly, the preparation and modification techniques to enhance their functionality and properties are further reviewed, the main physicochemical properties are introduced as well, highlighting their contributions to MCNs in applications. In addition, the biomedical applications of MCNs are emphasized, including tumor therapy, tumor theranostics, antibacterial, delivery of active molecules and biological detection. Finally, the prospects and challenges of clinical application based on MCNs are analyzed to provide an effective reference and lay the foundation for further research.
Promising TNF-α inhibitors: Targeting pathogenic TNF-α/TNFR signaling to restore Th17/Treg balance in rheumatoid arthritis
Jiajie Kuai, Zhuo Chen, Ju He, Fengling Wang, Wei Wei
, Available online  , doi: 10.1016/j.jpha.2025.101382
Abstract(118) HTML Full Text PDF(43)
Abstract:
The pleiotropic regulatory effect of tumor necrosis factor-alpha (TNF-α), an essential cytokine involved in immune regulation, is of significant importance in the immune response. TNF-α inhibitors have been widely used in rheumatoid arthritis (RA) and other autoimmune diseases since their introduction into clinical practice. However, the tradeoff between its excellent efficacy and adverse drug reactions (ADR) remains a problem. T cells, especially the T helper cell 17 (Th17)/regulatory T (Treg) cells balance, are crucial for the treatment of autoimmune diseases including RA. This review explores the mechanisms by which TNF-α/TNF receptor (TNFR) signaling induces Th17/Treg imbalance in RA. This review synthesizes current knowledge to facilitate an improved understanding of the causes of ADR, such as infection caused by TNF-α inhibitors in clinical practice. Moreover, our findings offer a reference for exploring potential TNF-α/TNFR signaling inhibitory strategies from the perspective of regulating T cell balance.
Breaking the boundaries of affinity selection-mass spectrometry: From ligand screening to target-ligand interaction insights
Pamella Christina Ortega de Oliveira, Bruno Sérgio do Amaral, Carmen Lucia Cardoso, Quezia Bezerra Cass, Marcela Cristina De Moraes
, Available online  , doi: 10.1016/j.jpha.2025.101379
Abstract(39) HTML Full Text PDF(1)
Abstract:
Affinity selection mass spectrometry (AS-MS) has emerged as a powerful label-free technique for identifying and characterizing ligand-target interactions. This review explores the diverse applications of AS-MS in drug discovery, including its role in selective screening, binding site characterization, and quantitative affinity determination. We discuss the use of AS-MS for determining equilibrium dissociation constants (KD) and competitive binding parameters (ACE50), highlighting its ability to rank ligand affinities efficiently. The review also examines AS-MS applications in fragment-based drug discovery, screening for molecular glues, and investigating interactions with membrane proteins. Moreover, we address key technical challenges, including competitive binding effects, protein stability, and ligand dissociation kinetics, along with recent advancements in automation and artificial intelligence (AI) integration. Rather than providing a comprehensive literature review, this work aims to broaden the applicability of AS-MS assays and encourage researchers to explore its use in underutilized contexts. By providing rapid and high-sensitivity affinity measurements, AS-MS continues to expand its role in drug discovery and structural biology, complementing conventional biophysical techniques.
USP50-mediated NLRP3 deubiquitination enhances NLRP3 inflammasome activation to suppress HCC metastasis
Zhengyan Gong, Yuhong Li, Yixuan Nie, Shenhao Zhang, Xiaoyu Tang, Yu Hu, Tianfeng Yang, Man Zhu, Wenjuan Tang, Qi Su, Yingzhuan Zhan, Dongdong Zhang, Bingling Dai, Yanmin Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101380
Abstract(91) HTML Full Text PDF(4)
Abstract:
The nucleotide-binding oligomerization domain (NOD)-like receptor protein 3 (NLRP3) inflammasome is downregulated in hepatocellular carcinoma (HCC), and its stability is regulated by ubiquitination. However, the regulatory mechanisms underlying NLRP3 deubiquitination and its role in HCC metastasis remains unclear. We demonstrated that ubiquitin-specific protease 50 (USP50) directly interacts with NLRP3, exhibiting deubiquitinase (DUB) activity through specific cleavage of K48-linked polyubiquitination chains to stabilize NLRP3 by preventing proteasomal degradation. Clinically, we observed that low NLRP3 and high β-catenin levels were negatively correlated in HCC specimens. Subsequent mechanistic exploration confirmed that NLRP3 exerts negative regulation on β-catenin by binding with glycogen synthase kinase 3 beta (GSK3β), reversing the downstream epithelial-mesenchymal transition (EMT) process, and inhibiting HCC metastasis. Notably, USP50 was found to activate NLRP3 inflammasome by promoting nuclear factor-kappa B (NF-κB) signaling, consequently enhancing proinflammatory cytokines. Furthermore, USP50 overexpression negatively regulated β-catenin, reversed EMT process and inhibited HCC metastasis in vivo. In conclusion, USP50 has emerged as a key player in regulating the NLRP3 inflammasome and inhibiting HCC metastasis by reversing the EMT process. As a result, it presents itself as a promising therapeutic target for HCC in the clinical setting. The intricacies of this regulatory mechanism, as revealed by our study, provide valuable insights into the understanding and potential interventions for HCC.
Latest surface plasmon resonance advances for G protein-coupled receptors
Giulia De Soricellis, Enrica Calleri, Sofia Salerno, Gloria Brusotti, Sara Tengattini, Caterina Temporini, Gabriella Massolini, Francesca Rinaldi
, Available online  , doi: 10.1016/j.jpha.2025.101381
Abstract(80) HTML Full Text PDF(0)
Abstract:
G protein-coupled receptors (GPCRs) are a big family of membrane proteins which represent one of the main classes of drug targets. However, their investigation presents several challenges, among which their instability outside the membrane environment. Different strategies for the drug discovery of this target are available, and surface plasmon resonance (SPR) stands out as one of the most informative and widespread binding assays, with many advantages such as real-time and label-free analyses resulting in the definition of both affinity and kinetic constants. This review covers the applications of SPR in GPCR drug discovery of the last 10 years and classifies the papers based on the immobilization strategy on the SPR sensor chip to maintain receptor stability. In particular, GPCR immobilization can occur in its native membrane by immobilizing whole cells or membrane fragments, using membrane mimetics (such as lipoparticles, lentiviral particles, liposomes, lipoproteins, nanodiscs, or planar lipid membranes) or immobilizing the isolated receptor stabilized by the use of detergents or engineering approaches. Different examples were considered and pros and cons of each strategy were presented.
Tumor-associated macrophages in hepatocellular carcinoma: Cellular plasticity and therapy resistance in crosstalk
Tianhao Zhang, Xi Zhao, Tingting Gao, Fang Ma
, Available online  , doi: 10.1016/j.jpha.2025.101384
Abstract(95) HTML Full Text PDF(2)
Abstract:
Hepatocellular carcinoma (HCC) is the predominant type of liver cancer. There are different risk factors for HCC including viral infection, liver fibrosis, non-alcoholic fatty liver disease, environmental factors and genomic alterations. The tumor microenvironment (TME) has been proposed as a potent regulator of tumor malignancy comprised of normal and cancerous cells. Macrophages are among the most abundant cells in the TME, known as tumor-associated macrophages (TAMs) that can control proliferation, metastasis, immune reactions and therapy response of tumor cells. In the present review, the function of TAMs in the regulation of HCC progression was evaluated. TAMs are prognostic factors in HCC that increase in TAM infiltration into TME can cause undesirable outcome in patients. Moreover, M2 polarization of macrophages can impair function of other immune cells such as T cells and natural killer cells to mediate immune evasion. TAMs demonstrate association with other biological events including autophagy and glycolysis. There is mutual interaction between TAMs and exosomes that TAM-mediated exosome secretion regulates HCC progression, while exosomes derived from other cells can also affect TAMs. Inhibition of macrophage recruitment, their depletion and increasing M1 polarization are promising approaches in HCC therapy. The natural products and nanostructures have been also recently introduced for the regulation of macrophages in HCC therapy.
Targeting SH3GL1 for Prognosis and Immune Response in Breast Cancer
Si Si, Hong Yu, Hao Zhang, Jianqiao Yin, Ziwei Li, Ning Wang, Xiaopeng Yu
, Available online  , doi: 10.1016/j.jpha.2025.101377
Abstract(41) HTML Full Text PDF(2)
Abstract:
The cuproptosis-related gene (CRG) SH3GL1 is identified as a pivotal regulator in breast cancer (BRCA) progression and immune regulation in this study. Through gene expression profiling and meta-analysis of public datasets, SH3GL1 was found to be overexpressed in BRCA tumor tissues and correlated with poor prognosis. Single-cell RNA sequencing pinpointed SH3GL1's expression in epithelial cells and its critical interactions with immune cells, particularly T cells and monocytes. Functional experiments confirmed SH3GL1’s role in promoting immune cell migration and modulating drug sensitivity. Moreover, high SH3GL1 expression was linked to reduced immunotherapy response, as revealed by TIDE scoring, suggesting its contribution to the immune microenvironment complexity in high-risk BRCA groups. These results emphasize SH3GL1's dual role as a prognostic biomarker and a target for therapeutic intervention in BRCA, providing new insights into personalized cancer treatment approaches.
Antimicrobial sonodynamic therapy: recent advances and challenges in new therapeutic approaches to antimicrobials
Linyu Xue, Shidian Ran, Jindie Huang, Xiaorui Wei, Xingrui Yan, Tongchuan He, Hongmei Zhang, Mengqin Gu
, Available online  , doi: 10.1016/j.jpha.2025.101375
Abstract(73) HTML Full Text PDF(4)
Abstract:
Pathogenic microorganisms pose significant threat to global health. In particular, conventional antibiotic treatments run the risk of exacerbating bacterial resistance. Antimicrobial sonodynamic therapy (aSDT), which combines sonosensitizers and low-intensity ultrasound (US), has opened up new avenues for the treating drug-resistant bacteria. The appeal of this therapy lies in its ability to focus US energy toward the deep-seated site of bacterial infection sites, it locally activates sonosensitizers and generates cytotoxic reactive oxygen species (ROS), which ultimately induces bacterial death. In the last decade, aSDT has been rapidly developed due to its good penetrative, biocompatibility and targeting properties. This paper highlights the recent aSDT advances in antimicrobial applications. We review aSDT mechanisms and sonosensitizers types, and propose relevant strategies to improve aSDT effects in terms of improving hypoxia and combining applications with other therapies. Furthermore, we summarize the potential obstacles and opportunities for the advancement of aSDT, and provide a deeper understanding of sonodynamic therapy (SDT) for antimicrobial applications, thereby promoting further innovation and clinical application.
Validation of breast cancer as a risk factor for anxiety and depression: insights from mendelian randomization analysis
Guannan He, Man Xi, Tianhao Zhang, Shuang Wang, Gang Liu
, Available online  , doi: 10.1016/j.jpha.2025.101378
Abstract(68) HTML Full Text PDF(0)
Abstract:
This study employed Mendelian randomization (MR) analysis to confirm the association between breast cancer and the risk of anxiety and depression, and to explore the molecular mechanisms by which lipid nanoparticles of ketamine (LNP@Ket) modulate these behaviors in a mouse model of breast cancer. Through single-cell transcriptomic analysis, the study aimed to clarify nuclear factor erythroid 2-related factor 2 (Nrf2)'s role in the development of anxiety and depression in these mice. Analysis of patient data from genome-wide association study (GWAS) databases supported the link between breast cancer, anxiety, and depression. In vivo experiments demonstrated that treating breast cancer mice with LNP@Ket significantly reduced anxiety and depression behaviors. The synthesis of LNP@Ket and its subsequent analysis highlighted its inhibitory effects on these behaviors. Single-cell transcriptomic sequencing identified key cells and genes affected by LNP@Ket treatment, particularly emphasizing Nrf2. Upregulation of Nrf2 in astrocytes increased the expression of antioxidant enzymes and reduced pro-inflammatory cytokines, alleviating anxiety and depression symptoms by inhibiting neuroinflammation and neurodegeneration. This comprehensive study highlights the pivotal role of Nrf2 in the therapeutic efficacy of LNP@Ket for treating anxiety and depression in breast cancer mice.
Synergistic antibacterial and anti-inflammatory potentials of dual-loaded self-healing hydrogel for methicillin-resistant Staphylococcus aureus-infected wound healing
Sangyu Hu, Weigang Zhong, Yuzhu Pei, Yutong Zhou, Jianfeng Wang, Xuming Deng, Zihao Teng, Lei Xu
, Available online  , doi: 10.1016/j.jpha.2025.101376
Abstract(50) HTML Full Text PDF(9)
Abstract:
The emergence of drug-resistant bacterial infection and persistent biofilm colonization pose a rigorous challenge to effective wound healing and regeneration, necessitating the innovative therapeutic strategies to combat these pressing clinical crises. Herein, nortriptyline, a novel FDA-approved tricyclic antidepressant was uncovered to effectively potentiate bactericidal activities of β-lactam antibiotics against methicillin-resistant Staphylococcus aureus (MRSA). Mechanistically, nortriptyline functions by disrupting the microbial iron homeostasis and potentiation of Fenton chemistry-mediated oxidative stress, concomitant with metabolic reprogramming via TCA cycle dysregulation and membrane destabilization. To enhance combination therapy-mediated therapeutic potential in wound management, the dual-loaded self-healing hydrogel OHA-PLL@AN was engineered to exhibit excellent biocompatibility and antibacterial potentials through molecular cross-linking of oxidized hyaluronic acid (OHA) and ε-polylysine (PPL). The therapeutic efficacy of OHA-PLL@AN was further validated in a murine model with MRSA-infected cutaneous wounds. OHA-PLL@AN therapy significantly attenuated the inflammatory response, concurrently promoting angiogenesis and accelerating the cutaneous wounds healing. Collectively, these findings underscore the dual drug-loaded self-healing hydrogel OHA-PLL@AN with anti-infection and anti-inflammatory properties as a novel therapeutic strategy for drug-resistant bacterial infected wounds therapy.
Luteolin attenuates RA-associated chronic pain by targeting the LDHA/H3K9la/NFATC2 axis to suppress Th17 cell differentiation and central infiltration
Yuepeng Jiang, Yang Zhao, Xiao Ma, Xiaoxuan Zhao, Mengjia Zheng, Junjun Wen, Cunrui Yuan, Xinyi Ding, Chengping Wen
, Available online  , doi: 10.1016/j.jpha.2025.101373
Abstract(79) HTML Full Text PDF(8)
Abstract:
Chronic joint pain in rheumatoid arthritis (RA) represents a persistent therapeutic challenge, and although luteolin (LUT) exhibits established anti-inflammatory properties, its precise mechanism for alleviating RA-associated chronic pain remains undefined. Through systematic investigation in collagen-induced arthritis (CIA) mice, we demonstrated that LUT administration effectively attenuated chronic pain by modulating spinal cluster of differentiation 4 positive T (CD4+ T) cell dynamics and suppressing microglial activation. Integrated multi-omics profiling (cleavage under targets and tagmentation, RNA sequencing (RNA-seq), and metabolomics) coupled with functional validation revealed nuclear factor of activated T cells 2 (NFATC2) as the central transcriptional regulator governing T helper 17 (Th17) cell differentiation and spinal infiltration through protein kinase C epsilon (PRKCE)-signal transducer and activator of transcription 3 (STAT3) signaling transduction. Significantly, our mechanistic studies uncovered a previously unrecognized epigenetic cascade: LUT-mediated suppression of lactate dehydrogenase A (LDHA) activity disrupts glycolysis-fueled histone h3 lysine 9 lactylation (H3K9la), thereby epigenetically silencing NFATC2 transcription. Translational studies using RA patient-derived CD4+ T cells confirmed LUT's capacity to normalize pathological hyperactivity of the LDHA/H3K9la/NFATC2 axis, concomitantly regulating CD4+ T dynamics. Biophysical validation through molecular docking, surface plasmon resonance, and molecular dynamics simulations established LUT's direct binding to LDHA with high affinity. Collectively, these findings delineate a novel therapeutic paradigm wherein LUT alleviates RA-associated chronic pain by orchestrating Th17 differentiation and migratory capacity through coordinated blockade of the LDHA-H3K9la-NFATC2 signaling network, highlighting its potential as a disease-modifying agent for chronic pain management in RA.
A comprehensive narrative review of Epimedium and its bioactive compounds in respiratory diseases
Lanlan Song, Changyu Lei, Cheng Zheng, Yichen Liu, Jian Liu, Dan Yao, Xiaoying Huang
, Available online  , doi: 10.1016/j.jpha.2025.101374
Abstract(68) HTML Full Text PDF(4)
Abstract:
Respiratory diseases pose a significant global health challenge due to their high morbidity and mortality rates. Traditional Chinese medicine (TCM), particularly the herb Epimedium, has demonstrated therapeutic potential in managing these diseases. This review systematically evaluates evidence from both in vitro and in vivo studies to assess the effects of Epimedium and its bioactive compounds, including Icariin (ICA), Icariside I (ICS I), Icariside II (ICS II), Icaritin (ICT), and others, on respiratory diseases. The synthesis of current literature reveals that these compounds exhibit anti-inflammatory, antioxidant, and immunomodulatory activities, as well as other effects crucial for the management of respiratory diseases. Further research is needed to fully understand and harness the therapeutic potential of Epimedium and its bioactive compounds in respiratory diseases.
Astrocytes: Unveiling their role in the molecular mechanism of natural antidepressants
Shimeng Lv, Ruirui Shang, Xia Zhong, Yitong Lu, Haonan Gao, Guangheng Zhang, Linghui Kong, Yunhao Yi, Yufei Huang, Yuexiang Ma, Jing Teng, Sheng Wei
, Available online  , doi: 10.1016/j.jpha.2025.101370
Abstract(31) HTML Full Text PDF(3)
Abstract:
Depression, an emotional disorder characterized by persistent low mood and loss of pleasure, can be alleviated by mainstream clinical drugs (such as selective serotonin reuptake inhibitors). However, issues such as delayed efficacy, significant individual differences, and adverse reactions remain. Compared to traditional single-target drugs, natural products have shown unique potential in depression intervention due to their synergistic multi-component effects and multi-target, multi-pathway regulation. As the most abundant glial cells in the central nervous system, astrocytes are deeply involved in the pathology of depression and have become important targets for the antidepressant effects of natural products. Although existing studies have revealed the regulatory effects of natural products on the function of astrocytes, there is still a lack of systematic categorization and mechanism integration. This review comprehensively summarized the molecular mechanisms by which natural products regulated astrocyte function through a systematic literature review, objectively analyzes key bottlenecks in current translational research, and aims to provide a theoretical basis and technical pathway for optimizing depression treatment paradigms and promoting the clinical translation of natural product research.
Mechanisms and therapeutic potential of YTHDF readers: linking epitranscriptomics to cancer
Na Deng, Qiang Sun, Shuying Wang, Shiheng Jia, Cheng Zheng, Fanglin Wang, Shuang Ma, Heng Zhou, Weiwei Liu
, Available online  , doi: 10.1016/j.jpha.2025.101371
Abstract(72) HTML Full Text PDF(6)
Abstract:
YT521-B homology domain-containing family paralogs (YTHDFs), as RNA epigenetic modification effector proteins, fully or partially participate in N6-methyladenosine (m6A), N1-methyladenosine (m1A), and 5-methylcytosine (m5C) modifications, which play critical roles in tumor biology and contribute to obtaining and maintaining cancer hallmarks relying on their characteristic protein structures. Accumulating evidence has underscored the involvement of YTHDFs in manipulating RNA stability, translation, and RNA metabolism, thereby influencing tumor initiation, progression, and anti-tumor treatment efficacy through independent RNA epigenetic modification pathways. This review aims to illustrate the essential regulatory mechanisms and pathological consequences of YTHDFs in tumorigenesis and therapeutic resistance. Additionally, we highlight the potential of targeting YTHDFs for cancer therapy, offering promising avenues for the elimination of tumor cells and the amelioration of tumor treatment efficacy.
Exploring TGFBR3 in disease pathogenesis: Mechanisms, clinical implications, and pharmacological modulation
Hui Song, Jinjiang Chou, Peng Zhao, Meijun Chen, Jue Yang, Xiaojiang Hao
, Available online  , doi: 10.1016/j.jpha.2025.101372
Abstract(148) HTML Full Text PDF(6)
Abstract:
Transforming growth factor beta (TGF-β) receptor 3 (TGFBR3), or betaglycan, is a transmembrane proteoglycan that serves as a coreceptor for TGF-β ligands, modulating TGF-β signaling in a context-dependent manner. Its extracellular domain can undergo proteolytic cleavage, yielding a 120 kDa soluble isoform (sTGFBR3) that antagonizes TGF-β signaling by sequestering ligands. Through this dual role, TGFBR3 exerts profound influence over various physiological and pathological processes, including cell survival, stemness, differentiation, cancer metastasis, chemoresistance, and fibrosis, underscoring its significance as both a biomarker and therapeutic target. Despite its significance, regulatory mechanisms, particularly tissue-specific expression, cross-talk with other pathways and post-translational modifications, remain poorly defined. A current thorough review of the prognostic and therapeutic implications of TGFBR3 is still lacking. In this review, we systematically examine the structural features of TGFBR3, and their functional relevance, providing an in-depth analysis of its dysregulation and molecular roles in diseases such as cancer, nervous system disorders, cardiovascular diseases (CVDs), diabetes and infectious diseases. Current experimental approaches are critically evaluated, and gaps in existing literature are highlighted to identify priorities for future research. By synthesizing emerging insights, this review aims to inform the development of TGFBR3-targeted therapies and support the design of innovative clinical and preclinical strategies.
Advances in aptamer technology for target-based drug discovery
Yingxian Cui, Yifan Chen, Youbo Zhang, Liqin Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101369
Abstract(149) HTML Full Text PDF(3)
Abstract:
Aptamer therapeutics represent a class of target-based therapies that leverage their high specificity and affinity for diverse molecular targets. As single-stranded DNA or RNA oligonucleotides, aptamers offer advantages in therapeutic applications. A critical aspect of aptamer drug development is the selection process, which has seen significant advancements through various in vitro selection methods, including Systematic Evolution of Ligands by Exponential Enrichment and its emerging variations. Recent progress has also introduced functional screening strategies that directly identify pharmacologically active aptamers, accelerating drug discovery. The applications of aptamers in disease treatment are expanding across oncology, neurodegenerative disorders, infectious diseases and other diseases. Aptamers exhibit versatile mechanisms of action, including blocking interactions, recruiting protein machinery, and inhibiting target functions. By addressing key limitations and presenting future directions, this review provides a comprehensive perspective on the recent evolving landscape of aptamer technology and its transformative potential in modern medicine.
Repurposing drugs for the human dopamine transporter through WHALES descriptors-based virtual screening and bioactivity evaluation
Ding Luo, Zhou Sha, Junli Mao, Jialing Liu, Yue Zhou, Haibo Wu, Weiwei Xue
, Available online  , doi: 10.1016/j.jpha.2025.101368
Abstract(75) HTML Full Text PDF(16)
Abstract:
Computational approaches, encompassing both physics-based and machine learning (ML) methodologies, have gained substantial traction in drug repurposing efforts targeting specific therapeutic entities. The human dopamine (DA) transporter (hDAT) is the primary therapeutic target of numerous psychiatric medications. However, traditional hDAT-targeting drugs, which interact with the primary binding site, encounter significant limitations, including addictive potential and stimulant effects. In this study, we propose an integrated workflow combining virtual screening based on weighted holistic atom localization and entity shape (WHALES) descriptors with in vitro experimental validation to repurpose novel hDAT-targeting drugs. Initially, WHALES descriptors facilitated a similarity search, employing four benztropine-like atypical inhibitors known to bind hDAT's allosteric site as templates. Consequently, from a compound library of 4,921 marketed and clinically tested drugs, we identified 27 candidate atypical inhibitors. Subsequently, ADMETlab was employed to predict the pharmacokinetic and toxicological properties of these candidates, while induced-fit docking (IFD) was performed to estimate their binding affinities. Six compounds were selected for in vitro assessments of neurotransmitter reuptake inhibitory activities. Among these, three exhibited significant inhibitory potency, with half maximal inhibitory concentration (IC50) values of 0.753 μM, 0.542 μM, and 1.210 μM, respectively. Finally, molecular dynamics (MD) simulations and end-point binding free energy analyses were conducted to elucidate and confirm the inhibitory mechanisms of the repurposed drugs against hDAT in its inward-open conformation. In conclusion, our study not only identifies promising active compounds as potential atypical inhibitors for novel therapeutic drug development targeting hDAT but also validates the effectiveness of our integrated computational and experimental workflow for drug repurposing.
Obtain Substance of Anti-glioblastoma from Erigeron breviscapus through Fragment-based Target Research (FBTR): An Efficient Strategy for Pharmacology Investigation and Optimization of Natural Products
Chunguo Wang, Jinli Shi, Qinling Rao, Bingqing Shen, Canyu Su, Heng Chen, Zhixing Huang, Shuwei Jiang, Rongge He, Luni Xu, Muxuan Li, Yonggang Liu, Tao Ma, Yantong Xu, Xinqi Deng
, Available online  , doi: 10.1016/j.jpha.2025.101366
Abstract(84) HTML Full Text PDF(2)
Abstract:
Natural products (NPs) make a major contribution to drug development, offering a huge molecule pool for drug leads. Nevertheless, the pharmaceutical industry and academy have declined their enthusiasm to NPs research since the great challenges in elucidating the complex component and intricate mechanism of NPs. Here, we introduce an efficient fragment-based target research (FBTR) approach for pharmacology study and optimization of NPs. Focusing on the core fragment within the molecules of NPs, we screen the outstanding activity that be triggered, and corresponding target. Finally, drug optimization was carried out around the molecules that obtaining the activity-related core fragment and verified both in vitro and in vivo. With this approach, we obtained an optimized NPs named Erigeron breviscapus polyphenols (EBP) with definite target. After optimization, Erigeron breviscapus polyphenols plus (EBPP) not only trigger immunogenic cell death (ICD) of glioblastoma (GBM) cells effectively by targeting to Cys105 amino acid site of Fas-associating protein with a novel death domain (FADD) protein, but also prolong the survival of GBM mice by an average of 17.6 days. Significantly, our investigation presents an approach for addressing challenges in NPs development and opening up new opportunities for drug discovery. Our findings demonstrate the utility of FBTR in exploring the function of NPs, revealing the target, and advancing drug optimization for stronger clinical translation.
Spatial metabolomics combined with machine learning in colon cancer diagnosis research
Ling Weng, Huanhuan Wang, Chunxiang Zhai, Qi Wang, Yanyan Guo, Ziyi Zhong, Chenying Ma, Jing Wang
, Available online  , doi: 10.1016/j.jpha.2025.101367
Abstract(108) HTML Full Text PDF(4)
Abstract:
Butyrate-based ionic liquid for improved oral bioavailability and synergistic anti-colorectal cancer activity of glycyrol
Ziyu Wang, Xingyue Shi, Yikang Shu, Ran Gao, Ting Sun, Mingyue Wu, Mingxin Dong, Weiguo Wu, Ruili Ma, Daoquan Tang, Min Ye, Shuai Ji
, Available online  , doi: 10.1016/j.jpha.2025.101359
Abstract(76) HTML Full Text PDF(6)
Abstract:
Pharmacological mechanisms of natural products with antidepressant effects: A focus on the programmed cell death regulation
Guangheng Zhang, Shimeng Lv, Shengchuan Bao, Weijie Zhao, Yunhao Yi, Haonan Gao, Xia Zhong, Xiangyu Li, Fengzhao Liu, Yitong Lu, Siyuan Sun, Jing Teng
, Available online  , doi: 10.1016/j.jpha.2025.101356
Abstract(89) HTML Full Text PDF(4)
Abstract:
Depression is a prevalent mental disorder characterized by persistent disinterest and a depressed mood, with severe cases potentially leading to suicide. In recent years, the incidence of depression has steadily increased, making it the second-largest global health burden. The pathogenesis of depression involves a series of complex pathological mechanisms, although the key underlying causes remain unclear. Programmed cell death (PCD), including apoptosis, autophagy, pyroptosis, ferroptosis, and necroptosis, involves highly organized gene expression processes that may influence the occurrence and development of depression by regulating cellular fate. Furthermore, numerous studies have shown that natural products can modulate PCDs through various signaling pathways, presenting significant potential for managing depression. Natural products offer benefits such as cost-effectiveness, fewer side effects, and other advantages, making them viable supplements or alternatives to traditional antidepressant drugs. To explore this potential, we reviewed studies demonstrating the antidepressant effects of natural products through multi-target modulation of PCDs. In addition, we discussed the toxicity and clinical applications of these natural products. This study highlights that diverse core biological pathways and targets are involved in determining the fate of depression-associated brain cells, including the PI3K/Akt signaling pathway, caspase-8, GSDMD, and others. In conclusion, the multi-target mechanisms of PCD regulation by natural products may provide a promising foundation for the future development of novel antidepressant medications.
Ferroptosis and retinal ganglion cell death in glaucoma: Mechanisms and therapeutic approaches
Minggao Qin, Xueqin He, Weiwen Qiu, Yanjing Peng, Yequan Liao, Jusen Zhao, Lianxiang Luo, Qiuli Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101355
Abstract(86) HTML Full Text PDF(2)
Abstract:
Glaucoma represents a predominant worldwide etiology of permanent vision impairment; it is clinically manifested through progressive neuronal atrophy in retinal ganglion cells (RGCs) and is accompanied by axonal degeneration in the optic pathway. Given the limited efficacy of conventional intraocular pressure-lowering therapies in halting RGC degeneration, the exploration of novel neuroprotective strategies has become imperative. An increasing amount of research emphasizes the pathogenic role of ferroptosis, a metal ion-associated programmed cellular demise mechanism recently implicated in neurodegenerative cascades, as a pivotal executor of RGC demise and putative central mechanism in glaucomatous pathology. This comprehensive review systematically examines the mechanistic interplay between ferroptosis and established contributors to glaucomatous optic neuropathy, including oxidative stress, mitochondrial dysfunction, glutamate excitotoxicity, and neuroinflammation. We provide evidence demonstrating that retinal ferroptosis is associated with the death of RGCs and discuss current therapeutic strategies to mitigate retinal ferroptosis, including treatments with natural products and gene therapy. Furthermore, by understanding ferroptosis, we provide insights into potential therapeutic targets and offer valuable directions for future research and clinical applications.
CXCL8/SDC1 Axis Mediates Tumor Stem Cell Interactions to Drive Remote Transfer in Thyroid Cancer
Wenjuan Wang, Jian Zhou, Baorui Tao, Ning Kong, Jie Shao
, Available online  , doi: 10.1016/j.jpha.2025.101354
Abstract(58) HTML Full Text PDF(7)
Abstract:
CRISPR screening redefines therapeutic target identification and drug discovery with precision and scalability
Yao He, Xiao Tu, Yuxin Xue, Yuxuan Chen, Bengui Ye, Xiaojie Li, Dapeng Li, Zhihui Zhong, Qixing Zhong
, Available online  , doi: 10.1016/j.jpha.2025.101357
Abstract(166) HTML Full Text PDF(20)
Abstract:
Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 screening technology is redefining the landscape of drug discovery and therapeutic target identification by providing a precise and scalable platform for functional genomics. The development of extensive single-guide RNA (sgRNA) libraries enables high-throughput screening (HTS) that systematically investigates gene-drug interactions across the genome. This powerful approach has found broad applications in identifying drug targets for various diseases, including cancer, infectious diseases, metabolic disorders, and neurodegenerative conditions, playing a crucial role in elucidating drug mechanisms and facilitating drug screening. Despite challenges like off-target effects, data complexity, and ethical or regulatory concerns, ongoing advancements in CRISPR technology and bioinformatics are steadily overcoming these limitations. Additionally, by integrating with organoid models, artificial intelligence (AI), and big data technologies, CRISPR screening expands the scale, intelligence, and automation of drug discovery. This integration boosts data analysis efficiency and offers robust support for uncovering new therapeutic targets and mechanisms. This review outlines the fundamental principles and applications of CRISPR screening technology, delves into specific case studies and technical challenges, and highlights its expanding role in drug discovery and target identification. It also examines the potential for clinical translation and addresses the associated ethical and regulatory considerations.
Development of a dual-chamber derivatization method for the determination of cyanide in sodium nitroprusside and its preparation via HS-GC-ECD
Jinqi Zheng, Xinyu Zhao, Caixia Li, Chenxiao Yan, Pingping Chen, Xiao Gu, Liya Hong, Su Zeng
, Available online  , doi: 10.1016/j.jpha.2025.101353
Abstract(78) HTML Full Text PDF(6)
Abstract:
The acute toxicity of cyanide and its pharmaceutical residues, has fueled interest in the development of analytical methods for its determination, particularly for sodium nitroprusside (SNP), a widely used vasodilator with potential cyanide residues. In this study, a dual-chamber derivatization bottle was designed to establish an interconnected gas environment, thereby facilitating chloramine T-mediated cyanide conversion to cyanogen chloride (CNCl) without direct contact with SNP. Subsequent determination of the analytes was undertaken using a headspace gas chromatography electron capture detector (HS-GC-ECD). The challenges of analyzing cyanide and the rapid degradation of SNP were addressed simultaneously. The method was subjected to rigorous validation, encompassing specificity, linearity, limits of detection (LOD), limit of quantification (LOQ), accuracy, precision, and robustness. The validation process revealed a notable degree of linearity within the range of 0.012-1.56 μg/mL, with a LOQ of 12.0 ng/mL. The method was found to be both accurate and precise, thus satisfying the requisite criteria. This method facilitates reliable cyanide monitoring in degradation-prone pharmaceuticals.
The role of NRF2 in human cancers: Pre-clinical insights paving the way for clinical trials
Yi Pei, Jianqiao Yin, Jiamei Liu, Dongze Liu, Qianlong Wu, Xue Cai, Mingming Han, Yu Tian, Liyu Yang, Shengye Liu
, Available online  , doi: 10.1016/j.jpha.2025.101358
Abstract(91) HTML Full Text PDF(5)
Abstract:
Tumorigenesis is viewed as a complex, multistep process in which genetic mutations play a crucial role. The genetic mutations cause notable changes, not only in the biological behavior of tumor cells but also in their reactions to treatment. Nuclear factor erythroid 2-related factor 2 (NRF2) is one of the most disrupted molecular pathways in human cancers, and during cancer development, the expression of this factor rises to enhance survival rates. The NRF2 seems crucial for shielding tumor cells from apoptosis and oxidative harm, while promoting pro-survival autophagy to increase the survival rate. Crucially, NRF2 plays a dual role in enhancing both the growth and metastasis of cancer cells, and the upregulation of this factor boosts the stemness and cancer-stem cell characteristics of tumor cells, while also promoting drug resistance and radioresistance. The elevation of glycolysis, activation of epithelial-mesenchymal transition (EMT), and inhibition of ferroptosis are additional features of NRF2 upregulation in human cancers. Among the different pathways that control NRF2, non-coding RNA transcripts play a significant role, and by altering NRF2 expression, they influence tumor development. The pharmacological modulation of NRF2 can occur through both direct and indirect methods; in the direct method, NRF2 is inhibited, whereas in the indirect method, the regulators and associated pathways of NRF2, like KEAP1, are influenced. The nanoparticles have been engineered to inhibit NRF2 in decreasing tumorigenesis. Consequently, the clinical application of current discoveries can enhance cancer treatment capabilities for patients in the near future
Phytomedicine-mediated time-dependent inactivation of CYP3A4 by chemical modification
Xu Mao
, Available online  , doi: 10.1016/j.jpha.2025.101352
Abstract(79) HTML Full Text PDF(3)
Abstract:
Cytochromes P450 (CYP)3A4 as the richest P450 enzyme is responsible for the metabolism of about 50% drugs. However, severe drug-drug interactions (DDIs) frequently occur when CYP3A4 is strongly inhibited by xenobiotics, which is one of the major reasons for the withdrawal of already marketed drugs. Compared to reversible inhibition, time-dependent inactivation (TDI), including mechanism-based inactivation (MBI), quasi-irreversible inactivation, and affinity-labeling inactivation, results from chemical modification of the host enzyme by electrophilic inactivators or electrophilic intermediates and is more likely to result in adverse clinical consequences. Increasing phytomedicines have been identified as time-dependent inactivators of CYP3A4 with the rapid growth of global consumption of natural products. According to vast experimental and theoretical studies, functional groups with chemical reactivity existing in phytomedicines are mainly involved in TDI of CYP3A4. For better understanding of the structure-activity relationship between phytomedicine and CYP3A4, we systematically summarize chemical mechanisms of TDI, including furan, thiophene, acetylenes, and methylenedioxyphenyl (MDP)-containing phytomedicineinduced MBI, MDP, alkylamine, and hydrazine-containing phytomedicine-induced quasi-irreversible inactivation, and iminium-containing phytomedicine-induced affinity-labeling inactivation, and comprehensively classify known natural CYP3A4 time-dependent inactivators, including polyphenols, alkaloids, terpenoids, and coumarins, which will offer the guidance and evidence for rational drug combinations and avoiding TDI-based DDIs in clinics.
A DPAL method for the identification of the synergistic target of drugs
Dongyao Wang, Yuxiao Tang, Na Li, Chenghua Wu, Jianxin Yang, Mengpu Wu, Feng Lu, Yifeng Chai, Chenqi Li, Hui Shen, Xin Dong, Changquan Ling
, Available online  , doi: 10.1016/j.jpha.2025.101351
Abstract(118) HTML Full Text PDF(17)
Abstract:
Pharmacokinetics, efficacy, and safety of a novel aripiprazole microsphere-based long-acting injectable formulation for schizophrenia: A multicenter, randomized controlled trial
An-Ning Li, Sheng-Chun Jin, De-Wei Shang, Jian-Xiong Guo, Hua-Li Lin, Ming Zhang, Bo Wei, Feng Wan, Yun-Long Tan, Li-Li Wang, Jian-Chu Zhou, Ping Liu, Lian-Lian Fan, Ju-Shui Sun, Bin Chen, Yimin Cui, Gang Wang
, Available online  , doi: 10.1016/j.jpha.2025.101350
Abstract(199) HTML Full Text PDF(15)
Abstract:
Recent advances in nanomaterial-based optical biosensors and their biomedical and biopharmaceutical applications
Mengjia Xu, Lutfun Nahar, Kenneth J. Ritchie, Chenxu Wang, Li Cheng, Zimiao Wu, Satyajit D. Sarker, Mingquan Guo
, Available online  , doi: 10.1016/j.jpha.2025.101349
Abstract(72) HTML Full Text PDF(5)
Abstract:
Optical biosensors are gaining popularity owing to their portability, miniaturization, no requirement for additional attachments and rapid responsiveness. These features render them suitable for various applications including at-home diagnostics, pharmacology, and continuous molecular monitoring. The integration of functionalized lowdimensional nanomaterials (zero-dimensional (0D), 1D, 2D, and 3D) has redirected focus towards the design, fabrication and optimization of optical biosensors. This review summarizes the fundamental mechanisms underlying optical biosensing. The key mechanisms include localized surface plasmon resonance (LSPR), photoluminescence (PL), surface enhancement Raman scattering (SERS), nanozymebased colorimetric strategies, chemiluminescence, bioluminescence and electrochemiluminescence. The advantages of various low-dimensional nanomaterials for different types of optical biosensors are presented. This comparison emphasizes their potential superiority in targeted biosensing applications. Therefore, promoting optical biosensing techniques and recent developments in advanced biosensing strategies for biomedical research and biopharmaceutical applications is necessary to establish their future directions.
Traditional Chinese medicine-facilitated redox-labile paclitaxel dimer nanoprodrug for efficient chemoimmunotherapy
Fan Li, Wenrui Wang, Weisheng Xu, WanYing Li, Yudi Lu, Rui Wang, Zhonggui He, Zhihui Feng, Jiabing Tong, Zhenbao Li
, Available online  , doi: 10.1016/j.jpha.2025.101348
Abstract(105) HTML Full Text PDF(4)
Abstract:
Various therapeutic modalities have been engineered for lung cancer treatment, but their clinic application is severely impeded by the poor therapy efficiency and immunosuppressive microenvironment. Herein, we fabricated a library of small molecule redox-labile nanoparticles (diPTX-2C NPs, diPTX-2S NPs, and diPTX-2Se NPs) by the self-assembly of dimer paclitaxel (PTX) prodrug, and then utilized these NPs with the traditional Chinese medicine (TCM) Qi-Yu-San-Long-Fang (Q) for effective chemoimmunotherapy on Lewis lung carcinoma (LLC)-bearing mice models. Under the high concentration of glutathione (GSH) and H2O2, diPTX-2Se NPs could specifically release PTX in cancer cells and exert a higher selectivity and toxicity than normal cells. In LLC tumor-bearing mice, oral administration of Q not only effectively downregulated programmed death ligand-1 (PD-L1) expression, but also remodeled the immunosuppressive tumor immune microenvironment via the increase of CD4+ T and CD8+ T cell proportion and the repolarization of M2 into M1 macrophages in tumor tissues, collectively achieving superior synergistic treatment outcomes in combination with intravenous PTX prodrug NPs. Besides, we found that the combination regimen also demonstrated excellent chemoimmunotherapeutic performances on low-dose small established tumor and high-dose large established tumor models. This study may shed light on the potent utilization of Chinese and Western-integrative strategy for efficient tumor chemoimmunotherapy.
An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph
Jian He, Yanling Wu, Linxi Yuan, Jiangguo Qiu, Menglong Li, Xuemei Pu, Yanzhi Guo
, Available online  , doi: 10.1016/j.jpha.2025.101347
Abstract(92) HTML Full Text PDF(6)
Abstract:
Computational analysis can accurately detect drug-gene interactions (DGIs) costeffectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.
A novel method for screening antihyperuricemic drugs by combining aptamer sensor array, exonuclease III-DNA walker and linear discriminant analysis
Shiquan Zheng, Jiale Ke, Hanren Chen, Huaze Shao, Fengxin Zheng, Runhui Zhang, Zean Zhao, Jianxin Pang, Lihong Liu
, Available online  , doi: 10.1016/j.jpha.2025.101345
Abstract(67) HTML Full Text PDF(0)
Abstract:
The lack of a cell-based screening method limits urate-lowering drug development. A novel method combining aptamer sensor array (ASA), exonuclease III (Exo III)- powered 3D DNA walker (DW), and linear discriminant analysis (LDA) was developed for detecting uric acid (UA) in cell lysates, referred to as ASA–Exo III-DW–LDA. Three aptamers (Apts) with different affinities for UA and its structurally similar compound, xanthine (Xan), were used to design the ASA. The combination of ASA and Exo III-DW enabled the detection of UA at the picomolar level, whereas LDA was employed to differentiate UA signals from the mixed signals of UA and Xan. Significantly, Pearson correlation analysis revealed a strong correlation between our method and the 14C radioactive labeling method for urate anion exchanger 1 (URAT1) inhibitors, with r = 0.9880 for lesinurad and r = 0.9777 for benzbromarone. Using our method, kaempferol was identified as a promising hit compound for inhibiting the URAT1, because of its low half-maximal inhibitory concentration (IC50) (18.96 μM) low toxicity in mouse renal tubular epithelial cells (mTECs), and significant uratelowering effect in hyperuricemic mice at 5 mg/kg. Overall, this method is sensitive, cost-effective and safe, offering a novel strategy for routine urate-lowering drug screening in standard laboratories.
Applications of quantitative 13C NMR in pharmaceutical analysis: From small molecule drugs to biopolymers
Qi Tang, Sinan Wang, Xiongqi Zhai, Seon Beom Kim, Prabhakar Achanta, Gonzalo R. Malca-Garcia, Yuzo Nishizaki, Yi Wang, Yu Tang
, Available online  , doi: 10.1016/j.jpha.2025.101346
Abstract(113) HTML Full Text PDF(6)
Abstract:
Chemical integrity is indispensable for advancing healthcare by ensuring the availability of high quality, safe, and effective pharmaceutical products. Ingredient quantification is particularly pivotal in this process. Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for both qualitative and quantitative analysis for complex systems. Compared with 1D quantitative 1H NMR (1H qNMR), quantitative 13C NMR (13C qNMR) holds some unique advantages. This technique offers a broader chemical shift range and the resulting much lesser signal overlap compare to 1H NMR spectroscopy. This review summarizes relevant studies on the use of 13C qNMR as a quantification technique, along with a focus on quantitative principles, influencing factors, and technical improvements of 13C NMR. The review also highlights its applicability in quantifying diverse molecular structures in pharmaceutical analysis. In addition, potential of low-field NMR, artificial intelligence (AI)-driven method development, and hyphenation of NMR with other techniques for 13C qNMR analysis is discussed and summarized as well. As a versatile method, 13C qNMR holds great potential, and ongoing research is expected to unlock its full capabilities and expand its range of applications.
Equivariant graph neural network-based accurate and ultra-fast virtual screening of small molecules targeting miRNA-protein complex
Huabei Wang, Zhimin Zhang, Guangyang Zhang, Ming Wen, Hongmei Lu
, Available online  , doi: 10.1016/j.jpha.2025.101339
Abstract(111) HTML Full Text PDF(8)
Abstract:
MicroRNAs (miRNAs) are small RNA molecules with significant therapeutic potential for treating various diseases, underscoring the need for effective methods to screen drugs targeting disease-associated miRNAs. In this study, we introduce miRPVS, a rapid virtual screening approach designed to identify small molecule drugs targeting miRNA-protein complex. miRPVS identifies binding pockets on the surface of these complexes, expanding the scope of potential small molecule targets. It employs an equivariant graph neural network model to extract 3D structure features of small molecules, enabling accurate prediction of docking scores. Using miRPVS, four complexes involved in pri-miRNA cleaving, pre-miRNA transport, and mRNA depress were identified as promising targets. For each target, hit compounds were screened from the ZINC20 database, which contains approximately 600 million druglike small molecules. MiRPVS predicted the docking score for these compounds, with Pearson correlation coefficients between predicted and experimentally docked scores comparable to those obtained through twice docking. Notably, the average deviation was only 0.67% across the four complexes. Remarkably, the entire screening process for all four complexes was completed in 14 h using just four V100 GPUs. Additionally, we integrated AlphaFold3-predicted structures into the miRPVS workflow, enabling virtual screening of small molecules against miRNA-protein complexes without experimentally determined structures. miRPVS demonstrated performance comparable to traditional docking methods while significantly reducing computational time and resource requirements. This innovative approach holds great promise for accelerating the discovery of small molecule drugs targeting miRNA-regulated pathways, addressing a critical gap in miRNA therapeutics.
Emodin is a novel phosphatidylethanolamine anabolism inhibitor that reprograms lipid metabolism to overcome 5-fluorouracil resistance in colorectal cancer
Yanyan Chen, Yanchen Liu, Zhicheng Gong, Zhaohui Huang
, Available online  , doi: 10.1016/j.jpha.2025.101343
Abstract(68) HTML Full Text PDF(152)
Abstract:
Screening of tyrosine phosphatase SHP2 (PTPN11) inhibitors from natural products with therapeutic potential for receptor tyrosine kinase-driven cancer
Lingfeng Chen, Di Ke, Zheng Jiang, Ruixiang Luo, Jie Li, Lulu Zheng, Guang Liang
, Available online  , doi: 10.1016/j.jpha.2025.101335
Abstract(74) HTML Full Text PDF(143)
Abstract:
Src homology 2 domain-containing phosphatase 2 (SHP2) is a pivotal regulator linking receptor tyrosine kinase (RTK) signaling. Abnormal SHP2 activity has been associated with tumorigenesis and metastasis. Although some SHP2-targeting modulators have entered clinical trials, FDA-approved SHP2 targeting drugs are still not available. Herein, we describe cooperative biochemical inhibition experiments that facilitate the identification of both catalytic and allosteric SHP2 inhibitors using an in-house natural product (NP) library. Based on this screening methodology, structurally diverse sets of NPs were characterized, among which dihydrotanshinone I (DHT) potently inhibited the wild-type SHP2 protein tyrosine phosphatase (PTP) domain and gain-of-function SHP2 variants. Trichostatin A (TSA) bound to the “tunnel” binding site, acting as an allosteric inhibitor. This study illustrates an optimized screening methodology and tactics to identify novel SHP2 modulators from NPs and provides a foundation for further NP-based drug development for the treatment of RTK-driven cancer.
A novel approach to assessing quality issues and component annotation in TCM prescription: Insights from 100 common TCM products
Huiting Ou, Chunxiang Liu, Saiyi Ye, Lin Yang, Qirui Bi, Wenlong Wei, Hua Qu, Yaling An, Jianqing Zhang, De-an Guo
, Available online  , doi: 10.1016/j.jpha.2025.101332
Abstract(114) HTML Full Text PDF(120)
Abstract:
The quality of traditional Chinese medicine (TCM) prescriptions (TCMPs) is critical to clinical efficacy; however, evaluating their consistency and identifying sources of variability remain challenging. This study proposes an integrated strategy to assess the quality of 100 widely sold TCMPs. A “one-for-all” chromatographic method was employed to analyze 645 sample batches. This large-scale data collection enabled statistical evaluations, such as hierarchical cluster analysis (HCA) and similarity heatmap, to identify quality inconsistencies. The introduction of a TCM-specific mass spectrometry (MS) database allowed for rapid, automated annotation of chemicals across 100 prescriptions and facilitated the tracing of raw material sources. Results indicate that 19% of prescriptions exhibited chemical inconsistencies, which are associated with high market value, low pricing, and substantial price disparities. The MS database allowed rapid annotation of 761 and 673 compounds in positive and negative modes, respectively, in 100 TCMPs, with 73 prescriptions reported for the first time. The tracing efforts succeeded in identifying >40% of the raw material sources for 51 prescriptions. P93 (Yinianjin) is a case in which the chromatographic profiles from three manufacturers displayed inconsistencies. Analysis using the database traced divergent peaks to Rhei Radix et rhizoma. Verification with self-prepared samples confirmed that manufacturers utilized three distinct botanical sources. This integrated strategy provides a scalable framework for quality control in TCMPs.
Naringenin boosts Parkin-mediated mitophagy via estrogen receptor alpha to maintain mitochondrial quality control and heal diabetic foot ulcer
Xin-Meng Zhou, Ying Yang, Dao-Jiang Yu, Teng Xie, Xi-Lu Sun, Ying-Xuan Han, Hai-Ying Tian, Qing-Qing Liao, Yu-Jie Zhao, Yih-Cherng Liou, Wei Huang, Yong Xu, Xi Kuang, Xiao-Dong Sun, Yuan-Yuan Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101333
Abstract(109) HTML Full Text PDF(120)
Abstract:
Diabetic foot ulcer (DFU) is an increasing global burden due to the rising prevalence of diabetes, and no specific pharmacological targets or satisfactory drugs are currently available for this devastating ailment. In this study, naringenin (NAR) was found to accelerate diabetic wound healing in diabetic C57BL/6J wild-type mice by reducing oxidative stress, as assessed through histological assay. NAR also alleviated the inhibition of proliferation, inflammation, cell senescence, and apoptosis in HaCaT cells induced by high glucose (HG). Mechanistically, the beneficial effects of NAR on wound healing are dependent on the E3 ubiquitin-protein ligase parkin. NAR upregulated the expression level of Parkin and promoted its mitochondrial translocation, thereby activating Parkin-mediated mitophagy and maintaining mitochondrial quality control (MQC). Moreover, the wound healing-promoting effects of NAR were significantly diminished in Parkin knockdown HaCaT cells and Prkn knockout DFU mice. Inhibition of NAR binding to estrogen receptors (ERs) using tamoxifen abolished the protective effects of NAR in HG-induced HaCaT cells. The luciferase reporter assay confirmed that NAR enhanced ERs binding to the estrogen response element (ERE), thereby upregulating Parkin transcription. Additionally, the cellular thermal shift assay revealed that NAR specifically bound to estrogen receptor alpha (ERα). In conclusion, NAR promoted DFU wound healing by enhancing Parkin-mediated mitophagy via binding to ERα, highlighting its potential as a promising therapeutic candidate.
Discovery of Selective HDAC6 Inhibitors Driven by Artificial Intelligence and Molecular Dynamics Simulation Approaches
Xingang Liu, Hao Yang, Xinyu Liu, Minjie Mou, Jie Liu, Wenying Yan, Tianle Niu, Ziyang Zhang, He Shi, Xiangdong Su, Xuedong Li, Yang Zhang, Qingzhong Jia
, Available online  , doi: 10.1016/j.jpha.2025.101338
Abstract(184) HTML Full Text PDF(19)
Abstract:
Increasing evidence showed that HDAC6 dysfunction is directly associated with the onset and progression of various diseases, especially cancers, making the development of HDAC6-targeted anti-tumor agents a research hotspot. In this study, artificial intelligence (AI) technology and molecular simulation strategies were fully integrated to construct an efficient and precise drug screening pipeline, which combined Voting strategy based on compound-protein interaction (CPI) prediction models, cascade molecular docking, and molecular dynamic (MD) simulations. The biological potential of the screened compounds was further evaluated through enzymatic and cellular activity assays. Among the identified compounds, Cmpd.18 exhibited more potent HDAC6 enzyme inhibitory activity (IC50 = 5.41 nM) than that of Tubastatin A ( TubA ) (IC50 = 15.11 nM), along with a favorable subtype selectivity profile (selectivity index ≈ 117.23 for HDAC1), which was further verified by the western blot analysis. Additionally, Cmpd.18 induced G2/M phase arrest and promoted apoptosis in HCT-116 cells, exerting desirable antiproliferative activity (IC50 = 2.59 μM). Furthermore, based on long-term MD simulation trajectory, the key residues facilitating Cmpd.18 ’s binding were identified by decomposition free energy analysis, thereby elucidating its binding mechanism. Moreover, the representative conformation analysis also indicated that Cmpd.18 could stably bind to the active pocket in an effective conformation, thus demonstrating the potential for in-depth research of the 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold.
Nanometer preparation of natural bioactive compounds for treatment of rheumatoid arthritis
Junping Zhu, Qin Xiang, Liu Li, Jiaming Wei, Rong Yu
, Available online  , doi: 10.1016/j.jpha.2025.101341
Abstract(97) HTML Full Text PDF(3)
Abstract:
Rheumatoid arthritis (RA) is a systemic autoimmune condition that leads to chronic arthritis, disability, and reduced lifespan. Current therapies show limited effectiveness and often cause severe side effects, with up to 50% of patients discontinuing disease-modifying antirheumatic drugs (DMARDs) due to unsatisfactory outcomes. Natural bioactive compounds (NBCs), such as glycosides, alkaloids, terpenoids, flavonoids, polyphenols, and coumarins, have gained attention for their immunomodulatory and anti-inflammatory properties. However, challenges like poor solubility, high dosage requirements, short action duration, and low tissue specificity hinder their clinical use. Nanoparticle (NP)-based delivery systems, including lipid NPs (LNPs), polymer carriers, and inorganic nanocarriers, have been designed to address these challenges through passive, active, and stimuli-responsive strategies. NBC-loaded NPs target immune dysfunction, synovial hyperplasia, bone destruction, angiogenesis, inflammation, and oxidative stress (OS) in RA. This review highlights recent advancements in NBCs for RA treatment, nanoformulation design, and targeted mechanisms, while addressing challenges and future directions in this field. The integration of cutting-edge nanotechnology has demonstrated significant potential to overcome traditional barriers such as low bioavailability and off-target effects through intelligent NPs design. Future research should enhance artificial intelligence (AI)-driven modeling to predict drug-nanocarrier interactions, develop biomarker frameworks for precision nanomedicine, and optimize RA management.
Quantifying compatibility mechanisms in traditional Chinese medicine with interpretable graph neural networks
Jingqi Zeng, Xiaobin Jia
, Available online  , doi: 10.1016/j.jpha.2025.101342
Abstract(53) HTML Full Text PDF(7)
Abstract:
Traditional Chinese medicine (TCM) features complex compatibility mechanisms involving multi-component, multi-target, and multi-pathway interactions. This study presents an interpretable graph artificial intelligence (GraphAI) framework to quantify such mechanisms in Chinese herbal formulas (CHFs). A multidimensional TCM knowledge graph (TCM-MKG;https://zenodo.org/records/13763953) was constructed, integrating seven standardized modules: TCM terminology, Chinese patent medicine (CPM), Chinese herbal pieces (CHPs), pharmacognostic origins (POs), chemical compounds, biological targets, and diseases. A neighbor-diffusion strategy was used to address the sparsity of compound-target associations, increasing target coverage from 12.0% to 98.7%. Graph neural networks (GNNs) with attention mechanisms were applied to 6,080 CHFs, modeled as graphs with CHPs as nodes. To embed domain-specific semantics, virtual nodes medicinal properties—therapeutic nature, flavor, and meridian tropism—were introduced, enabling interpretable modeling of inter-CHP relationships. The model quantitatively captured classical compatibility roles such as “sovereign-minister-assistant-courier,” and uncovered TCM etiological types derived from diagnostic and efficacy patterns. Model validation using 215 CHFs used for coronavirus disease 2019 (COVID-19) management highlighted Radix Astragali-Rhizoma Phragmitis as a high-attention herb pair. Mass spectrometry and target prediction identified three active compounds—Methylinissolin-3-O-glucoside, Corydalin, and Pingbeinine—which converge on pathways such as neuroactive ligand-receptor interaction, xenobiotic response, and neuronal function, supporting their neuroimmune and detoxification potential. Given their high safety and dietary compatibility, this herb pair may offer therapeutic value for managing long COVID-19. All data and code are openly available (https://github.com/ZENGJingqi/GraphAI-for-TCM), providing a scalable, interpretable platform for TCM mechanism research and discovery of bioactive herbal constituents.
DHGT-DTI: Advancing Drug-Target Interaction Prediction through a Dual-View Heterogeneous Network with GraphSAGE and Graph Transformer
Mengdi Wang, Xiujuan Lei, Ling Guo, Ming Chen, Yi Pan
, Available online  , doi: 10.1016/j.jpha.2025.101336
Abstract(50) HTML Full Text PDF(2)
Abstract:
Computational approaches for predicting drug-target interactions (DTIs) are pivotal in advancing drug discovery. Current methodologies leveraging heterogeneous networks often fall short in fully integrating both local and global network information. To comprehensively consider network information, we propose DHGT-DTI, a novel deep learning-based approach for DTI prediction. Specifically, we capture the local and global structural information of the network from both neighborhood and meta-path perspectives. In the neighborhood perspective, we employ a heterogeneous graph neural network, which extends Graph Sample and Aggregate (GraphSAGE) to handle diverse node and edge types, effectively learning local network structures. In the meta-path perspective, we introduce a Graph Transformer with residual connections to model higher-order relationships defined by meta-paths, such as "drug-disease-drug", and use an attention mechanism to fuse information across multiple meta-paths. The learned features from these dual perspectives are synergistically integrated for DTI prediction via a matrix decomposition method. Furthermore, DHGT-DTI reconstructs not only the DTI network but also auxiliary networks to bolster prediction accuracy. The experimental results demonstrate that DHGT-DTI achieves AUC values of 0.9603 and 0.9735 on Luo's dataset and Zeng's dataset, respectively, outperforming the baseline methods. Additionally, case studies on six drugs used to treat Parkinson's disease not only validate the practical utility of DHGT-DTI but also highlight its broader potential in accelerating drug discovery for other diseases.
Optimizing blood-brain barrier permeability in KRAS inhibitors: A Structure-constrained molecular generation approach equation
Xia Sheng, Yike Gui, Jie Yu, Yitian Wang, Zhenghao Li, Xiaoya Zhang, Yuxin Xing, Yuqing Wang, Zhaojun Li, Mingyue Zheng, Liquan Yang, Xutong Li
, Available online  , doi: 10.1016/j.jpha.2025.101337
Abstract(18) HTML Full Text PDF(1)
Abstract:
Kirsten rat sarcoma viral oncogene homolog (KRAS) protein inhibitors are a promising class of therapeutics, but research on molecules that effectively penetrate the blood-brain barrier (BBB) remains limited, which is crucial for treating central nervous system (CNS) malignancies. Although molecular generation models have recently advanced drug discovery, they often overlook the complexity of biological and chemical factors, leaving room for improvement. In this study, we present a structure-constrained molecular generation workflow designed to optimize lead compounds for both drug efficacy and drug absorption properties. Our approach utilizes a variational autoencoder (VAE) generative model integrated with reinforcement learning for multi-objective optimization. This method specifically aims to enhance BBB permeability while maintaining high-affinity substructures of KRAS inhibitors. To support this, we incorporate a specialized KRAS BBB predictor based on active learning and an affinity predictor employing comparative learning models. Additionally, we introduce two novel metrics, the knowledge-integrated reproduction score (KIRS) and the composite diversity score (CDS), to assess structural performance and biological relevance. Retrospective validation with KRAS inhibitors, AMG510 and MRTX849, demonstrates the framework’s effectiveness in optimizing BBB permeability and highlights its potential for real-world drug development applications. This study provides a robust framework for accelerating the structural enhancement of lead compounds, advancing the drug development process across diverse targets.
Unraveling pyrrolizidine alkaloid-induced liver damage with an integrative spatial lipidomics framework
Yilin Chen, Jie Xu, Thomas Ka-Yam LAM, Yanqiao Xie, Jianing Wang, Aizhen Xiong, Zhengtao Wang, Zongwei Cai, Linnan Li, Li Yang
, Available online  , doi: 10.1016/j.jpha.2025.101340
Abstract(59) HTML Full Text PDF(6)
Abstract:
Pyrrolizidine alkaloids (PAs), a class of secondary metabolites widely distributed in plants and the accidental ingestion or improper use of foods and herbs containing PAs, can lead to irreversible liver damage. Considering that the toxic mechanism of PAs is closely associated with metabolism, the hepatotoxicity was analyzed from the perspective of lipid metabolism. An integrated analytical approach was employed, combining mass spectrometry imaging (MSI) with liquid chromatography-mass spectrometry (LC-MS), to comprehensively investigate the spatial and temporal dynamics of lipid metabolites during PA exposure. The final lipidomics results combined with RNA sequencing showed that time-dependent changes in metabolite levels after the administration of PAs, involving the pathways of fatty acids, glycerophospholipids, glycerolipids and sphingolipids. Among them, phosphatidylcholines (PC), phosphatidylethanolamines (PE), phosphatidylinositols (PI) and sphingomyelins (SM) were downregulated to varying degrees within 0 to 24 h, while phosphatidylglycerol (PG), ceramides (Cer), diacylglycerols (DG) and triacylglycerols (TG) were upregulated. Notably, certain lipids exhibited distinct spatial distributions; for example, elevated levels of TG (56:13) were localized near the hepatic portal vein. Subsequently, the changes of lipid subclasses recovered within 24 to 48 h. Transcriptome RNA sequencing was used to enrich for key pathway-related differential genes Pemt, Gpat, etc. to explain the regulation of the hepatotoxic lipid pathway. The integration of MSI with LC-MS spectroscopy of endogenous metabolites provided intuitive insights into the alterations and spatial distribution of lipid metabolism in mice. Consequently, this study may enhance specific assessments and facilitate early diagnosis of acute toxicity associated with PAs.
A high throughput strategy for traditional Chinese medicine active compound screening based on Raman spectroscopy
Mengyin Tian, Xiaobo Ma, Yuandong Li, Hengchang Zang, Lian Li
, Available online  , doi: 10.1016/j.jpha.2025.101334
Abstract(95) HTML Full Text PDF(142)
Abstract:
Integrating Gas-Chromatographical Analyses with Nuclear-Magnetic-Resonance Spectroscopy to Elucidate Anti-microbial Profile of Oleoresins Isolated from Rauvolfia serpentina seeds by Supercritical-(CO2)-Fluid Extraction
Acharya Balkrishna, Monali Joshi, Yash Varshney, Manisha Kabdwal, Himanshu Jangid, Priya Rani M., Pardeep Nain, Savita Lochab, Anurag Varshney
, Available online  , doi: 10.1016/j.jpha.2025.101299
Abstract(83) HTML Full Text PDF(206)
Abstract:
Rauvolfia serpentina (L.) Benth. Ex Kurz is a greatly appreciated medicinal plant, well-known for its therapeutic benefits in traditional medicine, particularly in Ayurveda, where the roots and whole plant are used to treat a variety of ailments. However, studies focusing on R. serpentina seeds are relatively scarce. Hence, the present study provides a novel approach by analysing the seed oil of R. serpentina extracted using the supercritical-carbon dioxide-fluid-extraction (SCFE) technique. The research employed advanced analytical methods including gas-chromatography with flame ionization detector (GC-FID), gas-chromatography-tandem mass spectrometry (GCMS/MS), and high performance thin layer chromatography (HPTLC) to characterise the chemical composition of the extracted oil. Functional moieties were evaluated by Fourier transform infrared spectroscopy (FT-IR), while proton nuclear-magnetic-resonance (1H NMR) spectroscopy was utilised to identify the phytometabolites as well as to assess the physico-chemical parameters. The anti-microbial potential of the supercritically extracted oil was demonstrated through its activity against Klebsiella pneumoniae, Salmonella typhimurium, and Escherichia coli WP2 uvrA. The inhibitory effects on K. pneumoniae were quantified using the broth microdilution method, showing activity at both minimum inhibitory concentrations (MIC50 and MIC90). Furthermore, the oil was found to be non-genotoxic, as demonstrated by the Ames assay, which showed no mutagenic effects against S. typhimurium and E. coli WP2 uvrA. Since previous reports on R. serpentina seeds and their novel contribution in the field of pharmaceutics are rather limited, the present study is of utmost importance. The study may pave the way for future investigations into the therapeutic potentials of R. serpentina seeds.
Brain organoids-on-chip for neural diseases modeling: History, challenges and trends
Hongyong Zhang, Nan Huang, Sumin Bian, Mohamad Sawan
, Available online  , doi: 10.1016/j.jpha.2025.101323
Abstract(97) HTML Full Text PDF(137)
Abstract:
Brain organoid-on-chip platforms have emerged as groundbreaking tools in neural disease modeling and drug discovery, offering a unique and highly accurate simulation of human organ physiology and function compared with traditional cell culture systems. This technology is a harmonious fusion of organ-on-a-chip and organoid culture technologies, leveraging their strengths to provide the most realistic in vitro replication of the in vivo environment, both physically and biologically. As both technologies continue to advance rapidly, this platform is highly promising in vitro platform for disease modeling. In this review, we summarize the historical developments, recent advancements, limitations, and future prospects of brain organoid-on-chip technology, aiming to illuminate the transformative potential of this platform in advancing our understanding and treatment of neural diseases.
Structure-based design of anticancer drugs based on β-elemene: Research foundations and development potential
Haiyi Chen, Yuntao Yu, Chenghong Hu, Lehuang Zhou, Zhe Wang, Odin Zhang, Yi Wang, Tian Xie
, Available online  , doi: 10.1016/j.jpha.2025.101325
Abstract(81) HTML Full Text PDF(118)
Abstract:
β-elemene, a bioactive compound derived from traditional Chinese medicine (TCM), has been clinically used in cancer therapy. However, its molecular physicochemical properties require further optimization, and its precise anticancer mechanisms remain unknown. In modern drug development, structure-based drug design (SBDD) has significantly conserved resources, with computer-aided techniques such as molecular docking and molecule generation playing essential roles. A comprehensive review of existing molecular biology studies and virtual docking experiments led to the hypothesis that methyltransferase-like 3 (METTL3) may serve as a potential target of β-elemene. This discovery establishes a scientific foundation for integrating advanced, rational drug design strategies with β-elemene to enhance the therapeutic efficacy of TCM. Moreover, current artificial intelligence (AI)-based molecular generation models were examined, focusing on de novo molecular generation and lead optimization models. Their applications in the rational drug design of β-elemene were preliminarily explored to identify potential strategies for developing more potent anticancer derivatives by analyzing ligand-receptor interactions.
From foe to friend: Rewiring oncogenic pathways through artificial selenoprotein to combat immune-resistant tumor
Weiming You, Zhengjun Zhou, Zhanfeng Li, Jin Yan, Yang Wang
, Available online  , doi: 10.1016/j.jpha.2025.101322
Abstract(83) HTML Full Text PDF(15)
Abstract:
Reprogramming oncogenic signaling pathways to generate anti-tumor effects is a promising strategy for targeted cancer intervention, without significant off-target effects. Although reprogramming multi-oncoprotein interactions in a single signaling pathway axis has been shown to achieve sustained efficacy, there are several challenges that limit its clinical application. Herein, we transformed the mouse double minute 2 homolog (MDM2)-heat shock cognate protein 70 (HSC70) axis, a tumor-promoting pathway, into an activator of anti-tumor immunity using the Path-editor, an artificial selenoprotein. Once it enters the cell, Path-editor decomposes into PMI and PPI peptides: PMI inhibits MDM2-mediated p53 degradation and promotes HSC70 expression, while PPI binds to HSC70, enabling its ability to selectively degrade the programmed cell death ligand 1 (PD-L1). As a proof of concept, we tested its performance in microsatellite-stable (MSS) colorectal cancer, which typically displays limited responsiveness to immunotherapy. The results indicated that Path-editor effectively attenuated PD-L1 expression and reversed immune evasion in both CT26 allografts and humanized patient-derived tumor xenograft (PDX) models, thereby inhibiting tumor progression with high biosafety. Therefore, this paper introduces Patheditor as a paradigm for reprogramming oncogenic multi-protein pathways, utilizing selenium-assisted approach to achieve the rapid design of tumor-specific pathway editors. This strategy is expected to reverse immune escape in MSS colorectal cancer and treat difficult malignancies.
Identification of forsythoside A from Forsythia fruit for alleviating MAFLD via metabolic remodeling and IL-17 pathway regulation
Chenglin Song, Yuxi Huang, Xiaolin Sa, Linlin Wang, Mingju Yao, Zhengtong Jin, Yang Sun, Min Ye, Xue Qiao
, Available online  , doi: 10.1016/j.jpha.2025.101321
Abstract(178) HTML Full Text PDF(59)
Abstract:
In Vivo Analysis Techniques for Antibody Drug: Recent Advances and Methodological Insights
Xiaolu Miao, Beilei Sun, Jian Zhang, Jinge Zhao, Bing Ma, Yongming Li, Weizhi Wang
, Available online  , doi: 10.1016/j.jpha.2025.101314
Abstract(130) HTML Full Text PDF(16)
Abstract:
Antibody drugs, such as monoclonal antibodies and antibody-drug conjugates, have shown significant potential in treating diseases due to their high specificity and affinity. in vivo analysis of antibody drugs with non-invasive and real-time techniques is of importance to understand dynamic behavior of drugs within living organisms, and help evaluate their pharmacokinetics and efficacies. This review summarizes the advances and in vivo analysis methods of antibody drugs, including the techniques of radiolabeled imaging, near-infrared fluorescence imaging and surface-enhanced Raman spectroscopy. The principles, applications, and challenges of each technique are discussed, which provides insights for the development of antibody drugs and in vivo analytical methods.
Unlocking the potential of atractylenolide II: mitigating non-alcoholic fatty liver disease through farnesoid X receptor-endoplasmic reticulum stress interplay
Ming Gu, Zhiwei Chen, Yujun Chen, Yiping Li, Hongqing Wang, Ya-ru Feng, Peiyong Zheng, Cheng Huang
, Available online  , doi: 10.1016/j.jpha.2025.101318
Abstract(174) HTML Full Text PDF(23)
Abstract:
Evidences indicate that farnesoid X receptor (FXR) activation mitigates non-alcoholic fatty liver disease (NAFLD) by reducing endoplasmic reticulum (ER) stress. However, the mechanisms underlying FXR-ER stress interactions in combating NAFLD remain obscure. Moreover, few phytochemicals have been noted to improve NAFLD through this pathway. Here, we found that FXR activation directly induces the transcription of sarco/endoplasmic reticulum Ca2+ ATPase 2 (SERCA2), which acts as an ER stress repressor. This process leads to the dephosphorylation of the eukaryotic translation initiation factor 2 subunit α (eIF2α) within hepatocytes, consequently alleviating ER stress. Furthermore, through drug binding assays, luciferase reporter gene testing, gene expression analysis and biochemical evaluation, we identified the phytochemical atractylenolide II (AT-II) as a novel FXR agonist that effectively triggers SERCA2 activation. Our results showed AT-II effectively supresses accumulation of lipids and ER stress in palmitic acid-induced hepatocytes. In in vivo experiments, we demonstrated that AT-II attenuates fatty liver in diet- or chemical-induced NAFLD mouse models. Additionally, we showed that AT-II corrects diet-induced obesity, serum dyslipidemia, metabolic complications, and insulin resistance. Mechanistically, AT-II reduces ER stress, lipogenesis and inflammation and improves hepatic insulin signaling through stimulation of the hepatic FXR-SERCA2-eIF2α axis in mice. This conclusion was further reinforced by Serca2 knockdown both in vivo and in vitro, as well as FXR silencing in hepatocytes. Our findings provide new insights into the FXR-ER stress interplay in the control of NAFLD and suggest the potential of AT-II as an FXR agonist for the treatment of NAFLD through SERCA2 activation.
ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training
Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li, Yun Tang, Guixia Liu
, Available online  , doi: 10.1016/j.jpha.2025.101317
Abstract(81) HTML Full Text PDF(6)
Abstract:
Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid medicinal chemists in optimizing molecular structures. Nonetheless, they also form a major source of prediction error in structure-activity relationship (SAR) models. To date, several studies have demonstrated that deep neural networks based on molecular images or graphs might need to be improved further in predicting the potency of ACs. In this paper, we integrated the triplet loss in face recognition with pre-training strategy to develop a prediction model ACtriplet, tailored for ACs. Through extensive comparison with multiple baseline models on 30 benchmark datasets, the results showed that ACtriplet was significantly better than those deep learning (DL) models without pre-training. In addition, we explored the effect of pre-training on data representation. Finally, the case study demonstrated that our model's interpretability module could explain the prediction results reasonably. In the dilemma that the amount of data could not be increased rapidly, this innovative framework would better make use of the existing data, which would propel the potential of DL in the early stage of drug discovery and optimization.
DTLCDR: A target-based multimodal fusion deep learning framework for cancer drug response prediction
Jie Yu, Cheng Shi, Yiran Zhou, Ningfeng Liu, Xiaolin Zong, Zhenming Liu, Liangren Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101315
Abstract(93) HTML Full Text PDF(12)
Abstract:
Accurate prediction of drug responses in cancer cell lines (CCLs) and transferable prediction of clinical drug responses using CCLs are two major tasks in personalized medicine. Despite the rapid advancements in existing computational methods for preclinical and clinical cancer drug response (CDR) prediction, challenges remain regarding the generalization of new drugs that are unseen in the training set. Herein, we propose a multimodal fusion deep learning model called drug-target and single-cell language based CDR (DTLCDR) to predict preclinical and clinical CDRs. The model integrates chemical descriptors, molecular graph representations, predicted protein target profiles of drugs, and cell line expression profiles with general knowledge from single cells. Among these features, a well-trained drug-target interaction (DTI) prediction model is used to generate target profiles of drugs, and a pretrained singlecell language model is integrated to provide general genomic knowledge. Comparison experiments on the cell line drug sensitivity dataset demonstrated that DTLCDR exhibited improved generalizability and robustness in predicting unseen drugs compared with previous state-of-the-art baseline methods. Further ablation studies verified the effectiveness of each component of our model, highlighting the significant contribution of target information to generalizability. Subsequently, the ability of DTLCDR to predict novel molecules was validated through in vitro cell experiments, demonstrating its potential for real-world applications. Moreover, DTLCDR was transferred to the clinical datasets, demonstrating satisfactory performance in the clinical data, regardless of whether the drugs were included in the cell line dataset. Overall, our results suggest that the DTLCDR is a promising tool for personalized drug discovery.
Chemical Analysis, Antihyperglycemic Properties and Enzyme Inhibition of Opuntia dillenii: A Detailed Analysis of Juice and Peel Extracts
El Hassania Loukili, Amal Elrherabi, Asmae Hbik, Amine Elbouzidi, Mohamed Taibi, Mohammed Merzouki, Mohamed Bouhrim, Abdelaaty A. Shahat, Omar M. Noman, Abdellah Azougay, Bruno Eto, Mohamed Bnouham, Belkheir Hammouti, Mohammed Ramdani
, Available online  , doi: 10.1016/j.jpha.2025.101320
Abstract(37) HTML Full Text PDF(8)
Abstract:
Opuntia dillenii has been widely used in traditional medicine for various health conditions. This study examined the chemical composition of aqueous extracts from the plant's juice and peel and evaluated their effects on pancreatic α-amylase, lipase, and intestinal α-glucosidase enzymes, as well as their antihyperglycemic properties in vivo. Using High-Performance Liquid Chromatography with a Photodiode Array Detector (HPLC-DAD), significant variations in the composition were found between the plant's juice and peel, Key compounds included gallic acid, vanillic acid, p-coumaric acid, 3-hydroxy flavone, quercetin, cinnamic acid, kaempferol, and flavone. p-coumaric acid was highest in the juice (298.71±0.43 mg/100g) and peel (38.18±1.08 mg/100g), while flavone was higher in the peel (120.03±0.26 mg/100g). The extracts significantly inhibited pancreatic α-amylase and intestinal α-glucosidase in vitro, with confirmed in vivo effects reducing hyperglycemia in both healthy and diabetic rats. No toxicity was observed until the dose of 4000 mg/kg body weight. Molecular docking models showed that the plant's phytochemicals interacted with pancreatic enzymes more effectively than the drug acarbose. These findings highlight Opuntia dillenii's potential as a source of natural compounds with therapeutic properties, warranting further exploration.
Decoding protein dynamics with limited proteolysis coupled to mass spectrometry: A comprehensive review
Zilu Zhao, Xue Zhang, Xin Dong, Zhanying Hong
, Available online  , doi: 10.1016/j.jpha.2025.101319
Abstract(53) HTML Full Text PDF(2)
Abstract:
Proteins are indispensable to all biological systems and drive life processes through activities that are intricately linked to their three-dimensional structures. Traditional proteomics often provides static snapshots of protein expression, leaving unanswered questions about how proteins respond to stimuli and affect cellular functions. Limited proteolysis coupled with mass spectrometry (LiP-MS) has emerged as a powerful technique for exploring protein structure and function under near-natural conditions. Studies have revealed that LiP-MS is invaluable for structural and functional proteomics because it offers novel insights into protein dynamics. In this review, we summarise the current applications of LiP-MS in diverse areas such as the discovery and identification of drug targets, metabolite action mechanisms, proteome dynamics, protein interactions, and disease biomarkers. We also address the critical challenges in ongoing research and discuss their broader implications for advancing our understanding of protein biology and drug discovery. LiP-MS holds significant promise for accelerating biomarker and therapeutic target development as well as advancing molecular biology research in animals, plants, and microorganisms.
A Multimodal Contrastive Learning Framework for Predicting P-Glycoprotein Substrates and Inhibitors
Yixue Zhang, Jialu Wu, Yu Kang, Tingjun Hou
, Available online  , doi: 10.1016/j.jpha.2025.101313
Abstract(82) HTML Full Text PDF(4)
Abstract:
P-glycoprotein (P-gp) is a transmembrane protein widely involved in the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs within the human body. Accurate prediction of P-gp inhibitors and substrates is crucial for drug discovery and toxicological assessment. However, existing models rely on limited molecular information, leading to suboptimal model performance for predicting P-gp inhibitors and substrates. To overcome this challenge, we compiled an extensive dataset from public databases and literature, consisting of 5943 P-gp inhibitors and 4018 substrates, notable for their high quantity, quality, and structural uniqueness. In addition, we curated two external test sets to validate the model’s generalization capability. Subsequently, we developed a multimodal contrastive learning framework named MCPGP for predicting P-gp inhibitors and substrates. This framework integrates three types of features from Simplified Molecular Input Line Entry System (SMILES) sequences, molecular fingerprints, and molecular graphs using an attention-based fusion strategy to generate a unified molecular representation. Furthermore, we employed a graph contrastive learning approach to enhance structural representations by aligning local and global structures. Extensive experimental results highlight the superior performance of MC-PGP, which achieves improvements in the area under the curve of receiver operating characteristic (AUC-ROC) of 9.82% and 10.62% on the external P-gp inhibitor and external P-gp substrate datasets, respectively, compared with 12 state-ofthe-art methods. Furthermore, the interpretability analysis of all three molecular feature types offers comprehensive and complementary insights, demonstrating that MC-PGP effectively identifies key functional groups involved in P-gp interactions. These chemically intuitive insights provide valuable guidance for the design and optimization of drug candidates.
Targeting Atf4 for enhanced neuroprotection: Role of quercetin-loaded evs in ischemic stroke
Lanqing Zhao, Yu Chen, Xiaoxu Ding, Hongxi Li, Jinwei Li
, Available online  , doi: 10.1016/j.jpha.2025.101312
Abstract(54) HTML Full Text PDF(1)
Abstract:
This study investigates the neuroprotective potential of extracellular vesicles (EVs) delivering Quercetin-3-O-β-D-glucuronic acid (QG-EVs) in cerebral ischemia-reperfusion injury (CIRI). Targeted brain delivery of QG-EVs was confirmed, with neuron cells identified as pivotal in modulating CIRI through single-cell RNA sequencing (scRNA-seq). Activating transcription factor 4 (Atf4) was highlighted as a critical regulatory factor, and in vitro studies revealed that silencing Atf4 diminished the neuroprotective effects of QG-EVs, increasing oxidative stress levels and neuronal apoptosis. In a CIRI mouse model, the knockdown of Atf4 attenuated the protective outcomes provided by QG-EVs, further affirming the role of Atf4 in mediating neuroprotection. Behavioral assessments and protein analysis showed that QG-EVs significantly reduced neuronal damage and pro-apoptotic markers, while improving neurological function via Atf4 upregulation. The outcomes hint at the potential of QG-EVs as a beneficial therapeutic modality to mitigate neuronal damage in CIRI by enhancing Atf4 expression, highlighting its potential for improving ischemic stroke outcomes.
Reactivating T cell immunity in Wnt-hyperactivated non-small cell lung cancer through a supramolecular droplet of carnosic acid and peptide
Na Liu, Yuzhen Tu, Hanyu Wang, Xiaoqiang Zheng, Fanpu Ji, Mingsha Geng, Xin Wei, Jingman Xin, Wangxiao He, Qian Zhao, Tianya Liu
, Available online  , doi: 10.1016/j.jpha.2025.101309
Abstract(102) HTML Full Text PDF(7)
Abstract:
The Wnt/β-catenin signaling pathway is renowned for its contribution to the immunosuppressive microenvironment in non-small cell lung cancer (NSCLC). Consequently, inhibiting this pathway has emerged as a promising strategy to enhance immune activation and reinstate T cell responses in cancer treatment. In this study, we initially investigate the metabolic characteristics of Wnt-hyperactivated NSCLC using mass spectroscopic detection in a mouse in-situ model and unveil its significant feature of acid accumulation at tumor sites. Building upon this discovery, we design an acid-sensitive peptide-carnosic acid (CA) supramolecular droplet, Pep1@CA, which leverages the acidic microenvironment characteristic of NSCLC for controlled release. By doing so, we aim to enhance targeting efficiency while minimizing off-target effects. As anticipated, Pep1@CA demonstrates potent tumor-specific inhibition of the Wnt signaling pathway and effectively reactivates T cell immunity in Wnt-hyperactivated NSCLC. Importantly, comprehensive in vivo evaluations reveal significant antitumor efficacy alongside excellent biosafety profiles. Collectively, this study provides a therapeutic strategy with promising clinical translational potential for targeting the Wnt signaling pathway and offers theoretical support for its application in immunotherapy. This innovative approach underscores that targeting pathways beyond traditional immunotherapy can also activate tumor immunity, thereby expanding the potential of cancer immunotherapy.
Advancements in Plant-Derived Exosome-like Vesicles: Versatile Bioactive Carriers for Targeted Drug Delivery Systems
Haixia Shen, Shuaiguang Li, Liyuan Lin, Qian Wu, Zhonghua Dong, Wei Xu
, Available online  , doi: 10.1016/j.jpha.2025.101300
Abstract(84) HTML Full Text PDF(2)
Abstract:
Exosomes, small vesicles secreted by a wide range of cells, are found extensively in animals, plants, and microorganisms. Their excellent biocompatibility, efficient delivery capacity, and ease of membrane crossing have drawn significant interest as promising drug delivery carriers. Compared with their animal-derived counterparts, plant-derived exosomes (PDEs), in particular, stand out for their lower toxicity to human tissues, diverse sources, and enhanced targeted delivery capabilities. Advances in both in-depth research and technological development have enabled scholars to isolate exosomes successfully from various plants, exploring their potential in clinical therapies. However, the precise identification of PDEs and their drug delivery mechanisms remains an area of ongoing investigation. This review synthesizes the latest developments in the biogenesis, extraction, separation, and identification of PDEs, along with their engineering modifications and drug-loading strategies. We also delve into the therapeutic applications of exosomes and their future potential in drug delivery, aiming to elucidate the targeted delivery mechanisms of PDEs and pave new paths for clinical drug treatment.
Metabolomics-driven elucidation of the synergistic therapeutic mechanism of a novel SGLT-2/PPAR-γ dual receptor supramolecular system for treatment diabetes and obesity
Saisai Ren, Han Hao, Wei Guo, Mo Zhang, Honglin Feng, Jing Wang
, Available online  , doi: 10.1016/j.jpha.2025.101308
Abstract(98) HTML Full Text PDF(6)
Abstract:
A supramolecular system of active pharmaceutical ingredients (APIs) can modify the physicochemical properties and enhance the synergistic efficacy of their components; however, the relevant underlying mechanisms in vivo remain unclear. This study employed a metabolomics-driven approach, combined with biological validation, to investigate the synergistic mechanisms of API-based supramolecular systems. Metabolic dysfunction exacerbates insulin resistance and obesity, contributing to hepatic steatosis and cardiac hypertrophy. A novel sodium-dependent glucose transporter 2 (SGLT-2)/peroxisome proliferator-activated receptor-γ (PPAR-γ) dual receptor (dapagliflozin-pioglitazone (DAP-PIO)) supramolecular system was selected as the model to explore the synergistic mechanism involved in the treatment of metabolic dysfunctions, diabetes and obesity. First, metabolomics analyses were performed to compare the effects of a simple physical mixture (PM) of DAP and PIO with the DAP-PIO supramolecular system after absorption into the bloodstream. The results demonstrated significant differences, with the supramolecular system activating the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) and adenosine monophosphate-activated protein kinase (AMPK) signaling pathways. Ceramide (Cer), a key metabolite in sphingolipid metabolism, emerged as a critical mediator. Subsequently, the mechanisms underlying the DAP-PIO supramolecular system’s hypoglycemic effects and its ability to ameliorate hepatic steatosis and myocardial hypertrophy by reducing insulin resistance were evaluated and confirmed. These findings provide an innovative strategy for developing SGLT-2/PPAR-γ dual-receptor supramolecular systems to enhance the therapeutic outcomes for diabetes and obesity.
Oblique-incidence Reflectivity Difference Technology Identifies the Antiviral Drug Ribavirin as an Inhibitor of Lung Tumor Progression by Targeting AMPK Signaling
Jiani Gao, Yiwen Zheng, Yicheng Wang, Dong Xie, Yijiu Ren
, Available online  , doi: 10.1016/j.jpha.2025.101306
Abstract(75) HTML Full Text PDF(3)
Abstract:
Lung cancer takes the lead in terms of global cancer incidence and mortality rates. 5'-Adenosine monophosphate (AMP)-activated protein kinase (AMPK) serves as a universally conserved energy sensor throughout evolution checkpoint that orchestrates energy balance and metabolic homeostasis. However, AMPK activation has a complex, dual function in both the onset and advancement of lung cancer. Despite its protumorigenic effects, targeting AMPK with inhibitors to suppress cancer progression remains a critical area of research. An innovative high-content screening platform integrating small-molecule microarrays (SMMs) with oblique-incidence reflectivity difference (OI-RD) optical detection was established for AMPK inhibitor discovery. Alterations in the interfacial refractive index revealed that Ribavirin, an antiviral drug, has a high affinity for AMPK. Ribavirin binds directly to AMPK, suppressing its activation in mouse and human cells. By inhibiting AMPK phosphorylation, Ribavirin affects the downstream phosphorylation of mechanistic target of rapamycin complex 1 (mTORC1) and eukaryotic translation initiation factor 4E-binding protein 1 (4EBP1), thereby regulating tumor cell proliferation and apoptosis. These results identify Ribavirin as a new AMPK inhibitor with potential utility in lung cancer therapy.
1,8-Cineole ameliorates vascular endothelial senescence in diabetes mellitus by directly targeting and deubiquitinating PPAR-γ in vivo and in vitro
Lingyun Fu, Shidie Tai, Jiajia Liao, Youqi Du, Guangqiong Zhang, Die Guo, Xingmei Chen, Tian Zheng, Xiaoxia Hu, Wenbing Yao, Ling Tao, Xueting Wang, Yini Xu, Xiangchun Shen
, Available online  , doi: 10.1016/j.jpha.2025.101307
Abstract(61) HTML Full Text PDF(0)
Abstract:
Vascular endothelial senescence is an important pathophysiological factor in the development and exacerbation of cardiovascular health problems linked to diabetes mellitusn (DM). Accumulating evidence confirms that 1,8-cineole has multiple pharmacological properties, including anti-inflammatory, anti-microbial, and antioxidant activities. We investigated whether 1,8-cineole could ameliorate cardiovascular diseases and endothelial dysfunction, as the pharmacological properties and mechanism of diabetic vascular ageing remain unknown. Our results revealed notable senescence biomarkers in both in vivo and in vitro models. Treatment with 1,8-cineole alleviated lipid profiles and vascular senescence in mice with DM. Additionally, bioinformatics analysis suggested that peroxisome proliferator-activated receptor-γ (PPAR-γ) plays a crucial role in DM and ageing. We confirmed the binding capacity PPAR-γ with 1,8-cineole. Accordingly, experiments with the PPAR-γ agonist rosiglitazone, the PPAR-γ inhibitor GW9662, and PPAR-γ siRNA were performed to validate the pharmacological characteristics of 1,8-cineole. Finally, we clarified that 1,8-cineole can directly target PPAR-γ protein, as verified by cellular thermal shift assay, drug affinity responsive target stability, and surface plasmon resonance analyses. Taken together, these results provide the first evidence that 1,8-cineole ameliorates DM-induced vascular endothelial ageing via stabilising PPAR-γ protein by promoting deubiquitination at the Lys-466 site.
α-hederin decreases the glycolysis level in intestinal epithelial cells via SNX10-mediated DEPDC5 degradation
Hui Feng, Jin Wang, Lihuiping Tao, Liu Li, Minmin Fan, Chengtao Yu, Dongdong Sun, Haibo Cheng, Weixing Shen
, Available online  , doi: 10.1016/j.jpha.2025.101301
Abstract(67) HTML Full Text PDF(2)
Abstract:
Colorectal cancer (CRC) originates from biological events caused by gene mutations in normal intestinal epithelial cells (IECs). Sorting nexin 10 (SNX10) is a tumor suppressor in CRC that is involved in regulating chaperone-mediated autophagy (CMA) activity, which is implicated in the pathogenesis of CRC and glycolysis process. DEP domain containing 5 (DEPDC5) is a negative upstream regulator of mammalian target of rapamycin complex 1 (mTORC1). α-hederin has anti-CRC effects. We previously found that SNX10 knockdown in normal human IECs promoted glycolysis and decreased DEPDC5 expression, which was reversed by α-hederin. However, the specific mechanism has not yet been elucidated. Here, we aimed to investigate the specific regulatory mechanism of SNX10 on DEPDC5 expression, and the action of α-hederin on this process. We demonstrated that the degradation of DEPDC5 protein was accelerated after SNX10 knockdown, causing the activation of the mTORC1 pathway, which relied on CMA activation and lysosomal function enhancement. SNX10 interacted with DEPDC5 and recruited it to lysosomes for degradation, and the glycolysis level mediated by mTORC1 was elevated. Additionally, these phenotypes in shSNX10 IECs were compromised by SNX10 rescue. Moreover, α-hederin bound to the SNX10–DEPDC5 complex and impaired the interaction between SNX10 and DEPDC5, thereby inhibiting CMA-mediated DEPDC5 degradation, impairing the aberrant activation of mTORC1 signaling, and eventually reversing the elevation of glycolysis caused by SNX10 knockdown. Overall, we are the first to demonstrate that SNX10-mediated DEPDC5 degradation is a novel strategy for malignant transformation of normal human IECs, with α-hederin regulated during this process.
Virulence arresting drugs discovery by strategies targeting bacterial virulence: mainly focusing on quorum-sensing interference and biofilm inhibition
Lan Lu, Tianyang Yu, Hongping Wang, Xingtong Zhu, Li Liao, Jie Zhu, Xiaobo Wang, Andi Yang, Chen Yang, Yuping Zhang, Yulin Zhang, Kun Zou, Xiaorong Yang, Mingxing Li
, Available online  , doi: 10.1016/j.jpha.2025.101310
Abstract(63) HTML Full Text PDF(5)
Abstract:
The rising prevalence of multidrug-resistant pathogens poses a substantial threat to global healthcare systems, demanding urgent therapeutic interventions. Microorganisms exhibit diverse resistance mechanisms against various classes of antibiotics, highlighting the urgent need to discover novel antimicrobial agents for combating bacterial infections. Anti-virulence therapy has emerged as a promising therapeutic strategy that neutralizes pathogens by targeting their virulence determinants. The strategies for screening virulence arresting drugs (VADs) in bacteria represent a multifaceted approach that involves elucidating molecular pathogenesis mechanisms of bacterial pathogenicity, identifying evolutionarily conserved virulence factors across different pathogens, and employing integrated approaches combining in silico prediction with experimental validation. Recent technological advancements have established standardized protocols for effective identification and validation of anti-virulence compounds. This review systematically examines contemporary screening methodologies, primarily focusing on quorum-sensing disruption and biofilm suppression strategies, including in silico screening, activity-based screening with bioassays, in vitro and in vivo models. Additionally, we emphasize the imperative for standardized preclinical validation through physiologically relevant animal models, while proposing framework recommendations for developing next-generation VAD screening platforms. This synthesis not only outlines current best practices but also proposes innovative avenues for future antimicrobial discovery research.
Targeted Reduction-Responsive Nanovehicles for Photodynamic Therapy-Primed Immunotherapy in Melanoma
Chenqian Feng, Lingfeng Zhou, Bo Chen, Hui Li, Min Mu, Rangrang Fan, Haifeng Chen, Gang Guo
, Available online  , doi: 10.1016/j.jpha.2025.101311
Abstract(45) HTML Full Text PDF(2)
Abstract:
Melanoma, a common malignant skin tumor, faces challenges with multidrug resistance and high recurrence rates. Combining photodynamic therapy (PDT) and immunotherapy offers a promising personalized treatment approach. However, poor water solubility and significant side effects of photosensitizers and immune checkpoint inhibitors (ICIs) limit their application. Enhancing delivery efficiency while reducing adverse effects is crucial. Herein, we formulate BM@HSSC nanoparticles (NPs), which consist of a reduction-responsive hyaluronic acid (HA) backbone modified with photosensitizer Chlorin e6 (Ce6) and loaded with the programmed cell death-ligand 1 (PD-L1) inhibitor BMS-1. This system synergistically integrates PDT, immunogenic cell death (ICD), and immunotherapy for melanoma treatment. BM@HSSC NPs target and accumulate at the tumor site via the CD44 receptor. The disulfide bonds in the nanoparticles react with high GSH concentrations in tumor cells, rapidly releasing Ce6 and BMS-1. Under 660 nm laser irradiation, BM@HSSC NPs generate cytotoxic reactive oxygen species (ROS), inducing cell apoptosis and triggering ICD via. PDT Damage-associated molecular patterns (DAMPs) and tumor-associated antigens (TAAs) released from ICD promote dendritic cell (DC) maturation, enhancing antigen presentation and activating cytotoxic T lymphocytes (CTLs). Meanwhile, BMS-1 blocks the programmed cell death-1 (PD-1)/PD-L1 pathway, countering the immunosuppressive tumor microenvironment and inhibiting tumor cell immune escape. This strategy amplifies antitumor immune responses by enhancing immunogenicity and synergizing with ICIs, resulting in robust antitumor efficacy.
Sample preparation techniques for quality evaluation and safety control of medicinal and edible plants: Overview, advances, applications, and future perspectives
Lingxuan Ma, Lele Yang, Lijun Tang, Yudi Wang, Hua Luo, Zhangfeng Zhong, Wensheng Zhang, Di Chen, Jinchao Wei, Peng Li, Yitao Wang
, Available online  , doi: 10.1016/j.jpha.2025.101296
Abstract(60) HTML Full Text PDF(3)
Abstract:
Medicinal and edible plants (MEPs) have attracted increasing interest worldwide due to their natural origin, reliable efficacy, and minimal side effects in recent years. However, the complex and fluctuating levels of inherent chemical constituents and exogenous hazardous contaminants have triggered widespread concerns about their efficacy and safety. Developing analytical methods for both active components and exogenous contaminants concealed in these samples is central to the quality evaluation, in which sample preparation is crucial. This paper systematically reviewed the evolution of standard sample preparation methods, microextraction techniques based on novel solvents and nanomaterials, and innovative integrated techniques from 2019. Accordingly, their merits and weaknesses were discussed by showing fruitful applications in identifying and quantifying active components in these plants. Further, successful applications for analyzing exogenous contaminants were prominently showcased, highlighting the management of pesticides, heavy metals, mycotoxins, and polycyclic aromatic hydrocarbons. Finally, forthcoming trends in sample preparation techniques were delineated to illuminate the development and implementation of more advanced sample preparation technologies.
Regulation of Iron Metabolism in Ferroptosis: from Mechanism Research to Clinical Translation
Zhang Xin, Yang Xiang, Qingyan Wang, Xinyue Bai, Dinglun Meng, Juan Wu, Keyao Sun, Lei Zhang, Rongrong Qiang, Wenhan Liu, Xiang Zhang, Jingling Qiang, Xiaolong Liu, Yanling Yang
, Available online  , doi: 10.1016/j.jpha.2025.101304
Abstract(186) HTML Full Text PDF(5)
Abstract:
Iron is an essential trace element in the human body, crucial in maintaining normal physiological functions. Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process, a novel mode of programmed cell death characterized by iron overload and lipid peroxide accumulation. The iron metabolism pathway is one of the primary mechanisms regulating ferroptosis, as it maintains iron homeostasis within the cell. Numerous studies have demonstrated that abnormalities in iron metabolism can trigger the Fenton reaction, exacerbating oxidative stress, and leading to cell membrane rupture, cellular dysfunction, and damage to tissue structures. Therefore, regulation of iron metabolism represents a key strategy for ameliorating ferroptosis and offers new insights for treating diseases associated with iron metabolism imbalances. This review first summarizes the mechanisms that regulate iron metabolic pathways in ferroptosis and discusses the connections between the pathogenesis of various diseases and iron metabolism. Next, we introduce natural and synthetic small molecule compounds, hormones, proteins, and new nanomaterials that can affect iron metabolism. Finally, we provide an overview of the challenges faced by iron regulators in clinical translation and a summary and outlook on iron metabolism in ferroptosis, aiming to pave the way for future exploration and optimization of iron metabolism regulation strategies.
Perturbation response scanning of drug-target networks: Drug repurposing for multiple sclerosis
Yitan Lu, Ziyun Zhou, Qi Li, Bin Yang, Xing Xu, Yu Zhu, Mengjun Xie, Yuwan Qi, Fei Xiao, Wenying Yan, Zhongjie Liang, Qifei Cong, Guang Hu
, Available online  , doi: 10.1016/j.jpha.2025.101304
Abstract(0) HTML Full Text PDF(6)
Abstract:
Combined with elastic network model, the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the “therapeutic module” of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN corresponding to the module and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of HTR2B. Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.
GPT2-ICC: a data-driven approach for accurate ion channel identification using pre-trained large language models
Zihan Zhou, Yang Yu, Chengji Yang, Leyan Cao, Shaoying Zhang, Junnan Li, Yingnan Zhang, Huayun Han, Guoliang Shi, Qiansen Zhang, Juwen Shen, Huaiyu Yang
, Available online  , doi: 10.1016/j.jpha.2025.101302
Abstract(115) HTML Full Text PDF(1)
Abstract:
Current experimental and computational methods have limitations in accurately and efficiently classifying ion channels within vast protein spaces. Here we have developed a deep learning algorithm, GPT2 Ion Channel Classifier (GPT2-ICC), which effectively distinguishing ion channels from a test set containing approximately 239 times more non-ion-channel proteins. GPT2-ICC integrates representation learning with a large language model (LLM)-based classifier, enabling highly accurate identification of potential ion channels. Several potential ion channels were predicated from the unannotated human proteome, further demonstrating GPT2-ICC’s generalization ability. This study marks a significant advancement in artificial-intelligence-driven ion channel research, highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data. Moreover, it provides a valuable computational tool for uncovering previously uncharacterized ion channels.
Small-molecule probes based on natural products: Elucidation of drug-target mechanisms in stroke
Xingyue Jin, Suyi Liu, Shujing Chen, Rui Han, Xingyi Sun, Mingyan Wei, Yanxu Chang, Lin Li, Han Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101290
Abstract(49) HTML Full Text PDF(4)
Abstract:
Natural products (NPs) are an important source of new drugs for the treatment of stroke. Identifying cellular targets for bioactive molecules is a major challenge and critical issue in the development of new drugs for stroke. Small-molecule probes play a unique role in target discovery. However, drawbacks to these probes include non-specificity, unstable activity, and difficulty in synthesis. Small-molecule probes based on NPs at least partially compensate for these shortcomings. NPs feature rich chemical and structural diversity, biocompatibility, and unique biological activities. These features could be exploited to provide new ideas and tools for target discovery. Small-molecule probes based on NPs provide a precise and direct search for interacting protein targets of NPs-active small molecules. This review explores the properties of small-molecule probes based on NPs and their applications in mechanistic studies of stroke and other diseases. We hope that this review will bring new perspectives to the mechanistic study of NPs-active small molecules and accelerate the translation of these ingredients into drug candidates for the treatment of stroke.
Gut Microbiota-Bile Acid Metabolic Disorder Involved in the Cognitive Impairments in Epilepsy through HO-1 Dependent Ferroptosis
Xinyu Li, Jia Ji, Jing Li, Saisai Li, Qiang Luo, Maosheng Gu, Xin Yin, Meng Zhang, Hongbin Fan, Ruiqin Yao
, Available online  , doi: 10.1016/j.jpha.2025.101291
Abstract(72) HTML Full Text PDF(8)
Abstract:
Abnormal bile acid (BA) metabolism has been implicated in the pathogenesis of central nervous system (CNS) diseases, but its role in epilepsy remains unclear. In this study, we investigated the relationship between gut microbiota-driven dysregulation of BA metabolism and seizure-induced ferroptotic neuronal death in epilepsy. Our targeted metabolomic analysis revealed elevated levels of deoxycholic acid (DCA) in the serum and cerebrospinal fluid (CSF) of epileptic patients, which correlated with cognitive impairment. In a pentylenetetrazol (PTZ)-induced mouse model of epilepsy, 16S ribosomal RNA (16S rRNA) sequencing showed significant alterations in gut microbiota composition. Importantly, fecal microbiota transplantation (FMT) from healthy mice into epileptic mice significantly reduced seizure activity and improved cognitive function, primarily by normalizing serum and brain levels of secondary bile acids (SBAs), including DCA. Both in vitro and in vivo experiments demonstrated that DCA promotes ferroptosis in hippocampal neurons by activating the Farnesoid X Receptor (FXR). This activation triggered the nuclear factor erythroid 2-related factor 2 (Nrf2)-heme oxygenase-1 (HO-1) signaling pathway, known to be involved in oxidative stress and cell death regulation. Our findings suggest that the upregulation of DCA, through its effects on FXR and HO-1, plays a critical role in the progression of epilepsy by inducing ferroptosis in hippocampal neurons. Targeting the DCA-FXR-HO-1 axis may provide a novel therapeutic strategy for treating seizures and associated cognitive deficits in epilepsy.
Ursolic acid ameliorates ocular surface dysfunction in dry eye via targeting EGFR/RAS/RAF/MAP2K1/MAPK1 pathway
Qinghe Zhang, Ke Yan, Yufei Lv, Qiuping Liu, Yi Han, Zuguo Liu
, Available online  , doi: 10.1016/j.jpha.2025.101294
Abstract(115) HTML Full Text PDF(5)
Abstract:
Dry eye (DE), a multifactorial ocular surface disease, is predominantly characterized by inflammation as a central pathological factor. Ursolic acid (UA), a pentacyclic triterpenoid with well-documented anti-inflammatory properties, was evaluated in this study for its therapeutic effects on ocular surface dysfunction associated with DE and its underlying mechanisms. A hyperosmotic stress model (500 mOsM) using human corneal epithelial cells (HCEs) and an animal model of DE was established to assess UA's protective effects on both cellular and organismal levels. Comprehensive assessments, including phenol-red cotton tests and slit-lamp examinations, were performed to evaluate ocular surface damage in the DE mouse model. Potential UArelated targets and their relevance to DE pathology were identified through database mining. Protein-protein interaction (PPI) network construction and pathway enrichment analysis using the Metascape platform highlighted core targets and signaling pathways. Molecular docking simulations using AutoDock and PyMOL further elucidated the interaction modes between UA and its targets. To validate the molecular mechanisms underlying UA's therapeutic effects, integrative analyses were conducted using singlecell sequencing data from the Single Cell Portal and RNA sequencing of tissue samples. The results demonstrated that UA eye drops significantly preserved ocular surface functional units and alleviated DE symptoms, through modulation of the epidermal growth factor receptor (EGFR)/rat sarcoma (RAS)/rapidly accelerated fibrosarcoma (RAF)/mitogen-activated protein kinase kinase 1 (MAP2K1)/mitogen-activated protein kinase 1 (MAPK1) signaling pathway, as supported by network pharmacological analysis. Single-cell sequencing localized the distribution of key pathway proteins to the anterior ocular segment, particularly the cornea. In vivo experiments confirmed the therapeutic efficacy of UA eye drops via the EGFR/RAS/RAF/MAP2K1/MAPK1 pathway. Collectively, these findings underscore the potential of UA eye drops as a promising therapeutic approach for managing ocular surface disorders in DE.
Time-specific study on the efficacy of stems and leaves of Arachis hypogaea L. targeting glycine/serine metabolism for insomnia treatment
Yin Wang, Yuling Huang, Guohua Wang, Ting Jiang, Shuwen Geng, Hongzhan Xu, Tingting Zhou, Wenjing Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101288
Abstract(83) HTML Full Text PDF(2)
Abstract:
Recent insights into the roles and therapeutic potentials of GLS1 in inflammatory diseases
Jian-Xiang Sheng, Yan-Jun Liu, Jing Yu, Ran Wang, Ru-Yi Chen, Jin-Jin Shi, Guan-Jun Yang, Jiong Chen
, Available online  , doi: 10.1016/j.jpha.2025.101292
Abstract(87) HTML Full Text PDF(2)
Abstract:
Glutaminase 1 (GLS1) is a crucial enzyme that serves as the initial rate-limiting factor in glutaminolysis, a metabolic process that releases various factors that influence biological processes such as development, differentiation, and immune responses. Several studies have systematically investigated the crucial role of GLS1 in cancer. However, there is a lack of a comprehensive understanding of the relationship between GLS1 and inflammation. In this review, we present a detailed examination of GLS1, and discuss its structure, function, and role in inflammatory pathways. Here, we summarize the evidence supporting GLS1's involvement in several inflammatory diseases and explore the potential therapeutic applications of GLS1 inhibitors. We found that GLS1 plays a crucial regulatory role in inflammation by mediating glutaminolysis. Targeting GLS1, such as through the use of GLS1 inhibitors, can effectively alleviate inflammation induced by GLS1. Furthermore, we highlight the challenges and opportunities associated with investigating GLS1 function and developing targeted inhibitors, and propose practical solutions that offer valuable insights for the functional exploration and discovery of potential therapeutics aimed at treating inflammatory diseases.
Revolutionizing antibiotic therapy: polymyxin B and Fe2+-enriched liposomal carrier harness novel bacterial ferroptosis mechanism to combat resistant infections
Xiangrong Wei, Xinhui Cao, Chengyi Xu, Guangwei Shi, Hong Wang, Jinming Liu, Huiyang Li, Bingmei Yao, Yudong Zhang, Liqun Jiang
, Available online  , doi: 10.1016/j.jpha.2025.101293
Abstract(66) HTML Full Text PDF(7)
Abstract:
To address the pressing issue of bacterial resistance, antibiotics with new mechanisms were urgently needed; yet, the majority of efforts centered on discovering novel structural compounds, often plagued by lengthy research timelines and unpredictability. In this study, we introduce an alternative strategy that rejuvenates outdated antibiotics through a unique delivery system. Specifically, we leveraged polymyxin B (PMB) and created a liposomal carrier encapsulating PMB and Fe2+, designated P/Fe@L-P. When administered to PMB-resistant Acinetobacter baumannii, P/Fe@L-P triggered a downregulation of Nrf2 and GPX4 proteins, accompanied by a significant surge in reactive oxygen species and malondialdehyde levels, signifying the induction of ferroptosis. This mechanism imparted potent antibacterial activity, with P/Fe@L-P achieving minimal inhibitory and bactericidal concentrations of 54 and 192 μM, respectively, outperforming free PMB (72 and 768 μM). In vivo evaluations in mice models further validated the superior efficacy of P/Fe@L-P over PMB in treating PMB-resistant Acinetobacter baumannii pneumonia. This work establishes a highly effective and practical "old drug, new trick" paradigm, potentially expediting the fight against the escalating threat of bacterial resistance.
Recent advances in mass spectrometry-based bioanalytical methods for endogenous biomarkers analysis in transporter-mediated drug-drug interactions
Dang-Khoa Vo, Han-Joo Maeng
, Available online  , doi: 10.1016/j.jpha.2025.101289
Abstract(120) HTML Full Text PDF(4)
Abstract:
Drug-drug interactions (DDI) are a critical concern in drug development and clinical practice. A new molecular entity often requires numerous clinical DDI studies to assess potential risks in humans, which involves significant time, cost, and risk to healthy study participants. Consequently, there is growing interest in innovative techniques to improve the prediction of transporter-mediated DDI. Researchers in this field have focused on identifying endogenous molecules as biomarkers of transporter function. The development of biomarkers is notably more complex than that of exogenous drugs. Owing to their inherent selectivity, sensitivity, and ability to provide absolute quantification, liquid chromatography-mass spectrometry (LC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) are increasingly being employed for the quantitative investigation of new biomarkers. This review article presents recently developed bioanalytical approaches using LC-MS/MS for putative transporter biomarkers identified to date. Additionally, we summarize the published baseline endogenous levels of these potential biomarkers in a biological matrix to suggest a set of reference values for future research, thereby minimizing errors in biomarker-related data analyses or calculations.
Targeting Proteostasis Pathways for Cancer Therapy
Xiaofeng Dai, Ruohan Lyu, Guanqun Ge
, Available online  , doi: 10.1016/j.jpha.2025.101287
Abstract(68) HTML Full Text PDF(4)
Abstract:
The critical role of protein disequilibrium in driving carcinogenesis has long been recognized. Though several inhibitors of heat shock protein (HSP) family members have entered clinical trials, none of them have been approved for clinical use as a result of inevitable toxicity, leading to the identification of safer therapeutic approaches sharing a similar efficacy relevant and urgent. Through delineating the role of HSP90 inhibitors in arresting cancer hallmarks, this paper identified HSP90 inhibition as an effective therapeutic strategy capable of concomitantly targeting multiple key transformed properties of cancers via modulating cellular proteostasis. Through interrogating intrinsic connections between proteostasis and redox homeostasis, this paper proposed cold atmospheric plasma (CAP) as a possible alternative of HSP90 inhibitors with little adverse effects. This paper extended the therapeutic spectrum of HSP90 inhibitors and CAP to inflammation-driven pathologies including autoimmune diseases, as inflammation is a manifestation of failed proteostasis. These insights may conceptually advance our understandings on the driving force of cancers that can be easily extended to other disorders originated from imbalanced proteostasis and abnormal inflammation. Tools proposed here for inhibiting HSP90 including CAP and its possible synergy with HSP90 inhibitors may shift the current treatment paradigm to a new avenue in oncology and other relevant fields.
Metformin alleviates renal tubular injury in diabetic kidney disease by activating mitophagy and inhibiting ferroptosis via HIF-1α/MIOX signaling
Qinrui Wu, Yanyan Zhao, Fengjuan Huang
, Available online  , doi: 10.1016/j.jpha.2025.101284
Abstract(91) HTML Full Text PDF(4)
Abstract:
Renal tubular injury has emerged as a critical factor in the progression of diabetic kidney disease (DKD). Given renal tubules’ high mitochondrial density and susceptibility to mitochondrial dysregulation and ferroptosis, targeting these pathways could offer therapeutic potential. Metformin (MET), a first-line therapy for type 2 diabetes mellitus (T2DM), exerts reno-protective effects by improving mitochondrial function and attenuating fibrosis; however, its role in regulating ferroptosis in DKD remains unclear. This study aimed to investigate the role of MET in modulating mitophagy and ferroptosis in diabetic kidneys. In diabetic mouse models, MET notably alleviated tubular injury by promoting mitophagy and reducing ferroptosis, as shown by increasing levels of PTEN-induced putative kinase 1 (PINK1) and Parkin, while decreased levels of malondialdehyde (MDA) and iron content. Mechanistically, MET downregulated the hypoxia-inducible factor-1 alpha (HIF-1α)/myo-inositol oxygenase (MIOX) signaling axis in renal tubular epithelial cells (RTECs), thereby restoring mitophagy and inhibiting ferroptosis. These findings demonstrate that MET mitigates diabetic renal injury by promoting mitophagy and countering ferroptosis via suppressing the HIF-1α/MIOX pathway, highlighting its potential as a therapeutic intervention for halting DKD progression.
Regulated cell death in age-related macular degeneration: regulatory mechanisms and therapeutic potential
Le-Le Zhang, Jia-Mei Yu, Zhong-Xi Fan, Wen-Qi Xie, Liang Zou, Feiya Sheng
, Available online  , doi: 10.1016/j.jpha.2025.101285
Abstract(62) HTML Full Text PDF(2)
Abstract:
Age-related macular degeneration (AMD) represents a predominant cause of blindness among older adults, with limited therapeutic options currently available. Oxidative stress, inflammation, and retinal pigment epithelium injury are recognized as key contributors to the pathogenesis of AMD. Regulated cell death plays a pivotal role in mediating cellular responses to stress, maintaining tissue homeostasis, and contributing to disease progression. Recent research has elucidated several regulated cell death pathways—such as apoptosis, ferroptosis, pyroptosis, necroptosis, and autophagy—that may contribute in the progression of AMD owing to cell death in the retinal pigment epithelium. These discoveries open new avenues for therapeutic interventions in patients with AMD. In this review, we provide a comprehensive summary and analysis of the latest advancements regarding the relationship between regulated cell death and AMD. Moreover, we examined the therapeutic potential of targeting regulated cell death pathways for the treatment and prevention of AMD, highlighting their roles as promising targets for future therapeutic strategies.
Suppression of LIF in tumor-associated macrophages contributing to the PD-1/PD-L1 blockade in hepatocellular carcinoma
Shuangshuang Yin, Yanming Luo, Miaomiao Jiang, Lifeng Han, Sibao Chen, Leilei Fu, Yuling Qiu, Haiyang Yu
, Available online  , doi: 10.1016/j.jpha.2025.101286
Abstract(57) HTML Full Text PDF(3)
Abstract:
Mitochondrial membrane chromatography: Discovery of mitochondrial targeting modulators
Wu Su, Yu Kong, Hua Li, Yongyao Wang, Lizhuo Wang, Le Shi, Huaizhen He, Shengli Han, Hui Guo, Jiankang Liu, Jiangang Long
, Available online  , doi: 10.1016/j.jpha.2025.101272
Abstract(78) HTML Full Text PDF(1)
Abstract:
Mitochondria are fundamental organelles that play a crucial role in cellular energy metabolism, substance metabolism, and various essential cellular signaling pathways. The dysfunction of mitochondria is significantly implicated in the onset and progression of aging, neurodegenerative diseases, metabolic disorders, and tumors, thereby rendering mitochondria-targeted regulation, a vital strategy for disease prevention and treatment. The recently developed mitochondrial membrane chromatography (MMC) technique, which immobilizes mitochondrial proteins as a chromatographic separation medium, has shown great potential for efficiently screening mitochondria-targeted modulators from complex compound library. In contrast to traditional screening methods, MMC has no need to purify mitochondrial proteins and can preserve its in situ and physiological conformation. Consequently, it presents broader application prospects for screening mitochondrial modulators as well as investigating receptor-ligand interactions involving any target protein associated with mitochondria. This review aims to elucidate the critical role of mitochondria in the development and progression of major chronic diseases, discuss recent advancements and applications of MMC, and propose future directions for MMC in the identification of novel mitochondrial modulators.
Dexamethasone palmitate-loaded sHDL nanodiscs: Enhanced efficacy and safety in allergic conjunctivitis
Jiawei Li, Pengyue Liu, Yue Zhang, Fan Yang
, Available online  , doi: 10.1016/j.jpha.2025.101276
Abstract(63) HTML Full Text PDF(1)
Abstract:
Allergic conjunctivitis is a common ocular surface condition. Although corticosteroids are potent anti-inflammatory agents for its management, their use is often restricted by potential side effects. Conventional eye drops face challenges such as short retention time and poor corneal permeability, resulting in low drug bioavailability. To overcome these limitations, we developed a preservative-free synthetic high-density lipoprotein (sHDL) nanodisc eye drop containing dexamethasone palmitate. This novel formulation enhances drug stability and extends retention time on the ocular surface. In a mouse model of ovalbumin (OVA)-induced allergic conjunctivitis, the nanodisc eye drop significantly alleviated symptoms while reducing corticosteroid concentration, demonstrating excellent safety and biocompatibility. This innovative approach shows great promise for the treatment of allergic conjunctivitis and may lay the groundwork for new therapeutic strategies in anterior ocular disease management.
Tumor cells targetable graphene oxide doped microneedle for synergistic photothermal-chemotherapy treatment of melanoma
Zhiqiang Zhang, Junfang Ke, Yuxin Dai, Chenxi Fang, Yunfeng Dai, Chen Wang, Meitao Duan, Jungang Ren, Ming Chen
, Available online  , doi: 10.1016/j.jpha.2025.101270
Abstract(73) HTML Full Text PDF(0)
Abstract:
Melanoma is characterized by high malignancy, ranking the third among skin malignancies, and is associated with a lack of specific treatment options and poor prognosis. Therefore, the development of effective therapies for melanoma is imperative. A critical challenge in addressing subcutaneous disease lies in overcoming the skin barrier. In this study, we engineered a microneedle (MN) system that integrates chemotherapy, photothermal therapy (PTT), and targeted therapy to enhance anti-tumor efficacy while effectively penetrating the skin barrier. In vitro studies have demonstrated that the MN drug delivery system (DDS) can effectively penetrate the stratum corneum of the skin, deliver therapeutics to subcutaneous tumor sites, and establish a drug reservoir at these locations to exert anti-tumor effects. Cellular experiments indicated that the engineered PTT chemotherapy-targeted MNs can be internalized by tumor cells, exhibiting enhanced cytotoxicity against them. In vivo pharmacological investigations revealed that the combination of PTT and chemotherapy delivered via this MN DDS produced synergistic anti-tumor effects, achieving a tumor inhibition rate of up to 98.15%. This in situ DDS minimizes involvement with other organs, significantly reducing chemotherapy-related side effects. In summary, the PTT chemotherapy-targeted MNs developed in this study demonstrate promising application potential by enhancing anti-tumor efficacy while minimizing adverse effects.
A Multi-Omics-Empowered Framework for Precision Diagnosis and Treatment of Lysosomal Diseases
Nguyen Thi Hai Yen, Nguyen Tran Nam Tien, Nguyen Quang Thu, Franklin Ducatez, Wladimir Mauhin, Olivier Lidove, Soumeya Bekri, Abdellah Tebani, Nguyen Phuoc Long
, Available online  , doi: 10.1016/j.jpha.2025.101274
Abstract(81) HTML Full Text PDF(2)
Abstract:
Lysosomal diseases (LDs) are a group of rare inherited disorders belonging to inborn metabolism errors. LDs are characterized by the excessive storage of undegraded substrates, most often due to the enzymatic deficiency resulting from disease-causing gene variants. LDs lead to dysregulated cellular pathways and imbalanced molecular homeostasis and can affect multiple organs and tissues. Despite being rare, LDs account for a significant incidence when considered collectively. Due to complex molecular and genetic fingerprints, considerable challenges in LD management must be overcome. Diagnosis can be significantly delayed due to the broad and nonspecific clinical manifestations and the lack of specific biomarkers. Available treatments fail to fully stop the disease progression and can alter the disease’s typical phenotypes with novel manifestations. Therefore, a paradigm shift is crucial to better understand LDs and provide actionable insights. Herein, we comprehensively review the literature to demonstrate that multi-omics approaches are promising for pathophysiology elucidation, biomarker discovery, and precision therapy in LD. We recommend adopting longitudinal study designs integrated with a multi-omics-empowered framework to facilitate mechanistic delineation, biomarker discovery, and treatment development. Relevant approaches exploring the association between LDs and common neurodegenerative disorders are also discussed, paving a potential path for improved therapeutic development and ultimately improving the patient's quality of life.
Systematic review on the Extracellular Vesicles in Reproductive Medicine and Gamete Union
Yutao Wang, Honghao Sun, Fangdie Ye, Zhiwei Li, Zhongru Fan, Xun Fu, Yi Lu, Jianbin Bi, Hongjun Li
, Available online  , doi: 10.1016/j.jpha.2025.101261
Abstract(75) HTML Full Text PDF(2)
Abstract:
In this comprehensive review, we delve into the evolution of drug delivery systems in reproductive medicine with a focus on the emerging role of exosomes, a class of extracellular vesicles. Exosomes offer unique advantages in overcoming these challenges due to their inherent biocompatibility, stability, and ability to facilitate targeted delivery. This review provides a detailed examination of exosome biogenesis and their function in cellular communication, setting the stage for understanding their potential as drug delivery vehicles. We then explore the mechanisms through which exosomes can be loaded with small molecule drugs and the benefits they offer over synthetic nanoparticles. The review highlights groundbreaking case studies that illustrate the successful application of exosome-mediated drug delivery in reproductive health, including enhancing fertility treatments, supporting gamete and embryo development, and facilitating maternal-fetal communication. This study aims to provide a precise understanding of how exosomal drug delivery can revolutionize treatments for reproductive health disorders, paving the way for future therapeutic applications. Lastly, we touch upon the promising therapeutic implications of exosomal delivery for proteins and genes, offering a window into future treatments for reproductive health disorders.
Signatures of proteomics and glycoproteomics revealed liraglutide ameliorates MASLD by regulating specific metabolic homeostasis in mice
Yuxuan Chen, Chendong Liu, Qian Yang, Jingtao Yang, He Zhang, Yong Zhang, Yanruyu Feng, Jiaqi Liu, Lian Li, Dapeng Li
, Available online  , doi: 10.1016/j.jpha.2025.101273
Abstract(49) HTML Full Text PDF(3)
Abstract:
Liraglutide (Lira), a glucagon-like peptide-1 (GLP-1) receptor agonist approved for diabetes and obesity, has shown significant potential in treating metabolic dysfunction-associated steatotic liver disease (MASLD). However, its systematic molecular regulation and mechanisms remain underexplored. In this study, a mouse model of MASLD was developed using a high-fat diet (HFD), followed by Lira administration. Proteomics and glycoproteomics were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS), while potential molecular target analysis was conducted via quantitative real-time polymerase chain reaction (qPCR) and Western blotting. Our results revealed that Lira treatment significantly reduced liver weight and serum markers, including alanine aminotransferase (ALT) and others, with glycosylation changes playing a more significant role than overall protein expression. The glycoproteome identified 255 independent glycosylation sites, emphasizing the impact of Lira on amino acid and carbohydrate metabolism, and ferroptosis. Simultaneously, proteomic analysis highlighted its effects on lipid metabolism and fibrosis pathways. 21 signature molecules, including 7 proteins and 14 N-glycosylation sites, were identified as potential targets. A Lira hydrogel formulation (Lira@fibrin (Fib) Gel) was developed to extend drug dosing intervals, offering enhanced therapeutic efficacy in managing chronic metabolic diseases. Our study demonstrated the importance of glycosylation regulation in the therapeutic effects of Lira on MASLD, identifying potential molecular targets and advancing its clinical application for MASLD treatment.
Artificial intelligence guided Raman spectroscopy in biomedicine: Applications and prospects
Yuan Liu, Sitong Chen, Xiaomin Xiong, Zhenguo Wen, Long Zhao, Bo Xu, Qianjin Guo, Jianye Xia, Jianfeng Pei
, Available online  , doi: 10.1016/j.jpha.2025.101271
Abstract(65) HTML Full Text PDF(1)
Abstract:
Due to its high sensitivity and non-destructive nature, Raman spectroscopy has become an essential analytical tool in biopharmaceutical analysis and drug development. Despite of the computational demands, data requirements, or ethical considerations, artificial intelligence (AI) and particularly deep learning algorithms has further advanced Raman spectroscopy by enhancing data processing, feature extraction, and model optimization, which not only improves the accuracy and efficiency of Raman spectroscopy detection, but also greatly expands its range of application. AI-guided Raman spectroscopy has numerous applications in biomedicine, including characterizing drug structures, analyzing drug forms, controlling drug quality, identifying components, and studying drug-biomolecule interactions. AI-guided Raman spectroscopy has also revolutionized biomedical research and clinical diagnostics, particularly in disease early diagnosis and treatment optimization. Therefore, AI methods are crucial to advancing Raman spectroscopy in biopharmaceutical research and clinical diagnostics, offering new perspectives and tools for disease treatment and pharmaceutical process control. In summary, integrating AI and Raman spectroscopy in biomedicine has significantly improved analytical capabilities, offering innovative approaches for research and clinical applications.
Epimedii Folium flavonoids: A double-edged sword effect on the liver, a dual exploration of efficacy and toxicity
Meijun Yue, Yanlu Liu, Xiaoan Feng, Bo Cao, Xiaofei Fei, Guohui Li, Chunyu Li
, Available online  , doi: 10.1016/j.jpha.2025.101269
Abstract(184) HTML Full Text PDF(5)
Abstract:
Flavonoids, the key active compounds in Epimedii Folium, have both protective and toxic effects on the liver. Their hepatoprotective effects are associated with reducing lipid accumulation and oxidative stress, which contribute to the management of various liver conditions. In contrast, the mechanisms driving Epimedii Folium-induced hepatotoxicity are less understood but likely involve oxidative stress and pyroptosis. Pharmacokinetic studies, especially on icaritin, indicate that it undergoes isopentenyl dehydrogenation, glycosylation, and glucuronidation in vivo, contributing to its pharmacological effects. However, intermediate metabolites of icaritin may interact with biomolecules, potentially leading to liver toxicity. This review offers a detailed examination of the dual effects of Epimedii Folium flavonoids on liver function, emphasizing recent discoveries in their hepatoprotective and hepatotoxic pathways. We also summarize and discuss the pharmacokinetics of these flavonoids, highlighting how their metabolism affects therapeutic efficacy and toxicity. Lastly, we propose strategies to mitigate liver injury, providing new perspectives on the safe use of Epimedii Folium.
A Customizable Continuous and Near Real-time TEER Platform to Study Anti-cancer Drug Toxicity in Barrier Tissues
Jones Curtis G., Chen Chengpeng
, Available online  , doi: 10.1016/j.jpha.2025.101266
Abstract(60) HTML Full Text PDF(2)
Abstract:
Barrier tissues such as the endothelium are critical in the regulation of mass transfer throughout the body. Trans-endothelium/epithelium electrical resistance (TEER) is an important bioelectrical measurement technique to monitor barrier integrity. Although available on the market, TEER sensors are usually expensive and bulky and do not allow customization around experimental setups like specific microfluidic settings. We recently reported a customizable TEER sensor built on Arduino. In this paper, we significantly advanced a new generation of TEER sensors characterized by 1) a large dynamic range of 242-11,880 Ω·cm2 with high accuracy (> 95%), which covers common needs for TEER studies, 2) a coupling 3D-printed microfluidic system enabling modular cell integration and flow-based barrier studies, 3) customizable on-off cycles to significantly reduce cell exposure to the current, and 4) automated continuous measurements with customizable intervals. With this sensor system, we investigated how doxorubicin could impair the endothelium layer’s permeability, at a 1-min interval for 24 h. Endothelium toxicity is a new research direction under cardiotoxicity, with many aspects unknown. We found that a clinically relevant dosage did not change the endothelium integrity significantly until approximately 16 h of treatment, after that, the TEER started to drop (showing higher permeability), followed by a slight restoration of its barrier integrity. With an excess dosage (2.5 µM), the TEER started to drop significantly after 5 h and did not show recovery afterward, indicating endothelium toxicity. Overall, we report a new TEER sensor that can monitor continuous drug toxicity on barrier tissues. The customizable features make it translational for various other studies, such as personalized dosage determination on stem cell-derived tissue barriers, and transient barrier permeability variations under diseased conditions.
Predicting cardiotoxicity in drug development: A deep learning approach
Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han
, Available online  , doi: 10.1016/j.jpha.2025.101263
Abstract(124) HTML Full Text PDF(13)
Abstract:
Cardiotoxicity is a critical issue in drug development that poses serious health risks, including potentially fatal arrhythmias. The human ether-à-go-go related gene (hERG) potassium channel, as one of the primary targets of cardiotoxicity, has garnered widespread attention. Traditional cardiotoxicity testing methods are expensive and time-consuming, making computational virtual screening a suitable alternative. In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), Knearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. Our models demonstrated advanced predictive performance. The best machine learning model, XGBoost Morgan, achieved an accuracy (ACC) value of 0.84, and the deep learning model, Transformer_Morgan, achieved the best ACC value of 0.85, showing a high ability to distinguish between toxic and non-toxic compounds. On an external independent validation set, it achieved the best area under the curve (AUC) value of 0.93, surpassing ADMETlab3.0, Cardpred, and CardioDPi. In addition, we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods, such as voting and stacking, provided slight improvements in model stability. Furthermore, the SHapley Additive exPlanations (SHAP) explanations revealed the relationship between benzene rings, fluorine-containing groups, NH groups, oxygen in ether groups, and cardiotoxicity, highlighting the importance of these features. This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and sf method for drug safety assessment. Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.
Biomarkers of bipolar disorder in omics and neuroimaging
Donglin He, Jingzhi Yang, Zuowei Wang, Xin Dong
, Available online  , doi: 10.1016/j.jpha.2025.101264
Abstract(93) HTML Full Text PDF(6)
Abstract:
Bipolar disorder (BD) affects 1% of the global population. BD is a group of chronic psychiatric disorders characterized by recurrent manic or hypomanic episodes that may alternate with depressive episodes. Given the current diagnostic modalities, accurately diagnosing BD, particularly distinguishing it from unipolar depression (UD), is challenging. Biomarkers have emerged as potent instruments for establishing objective diagnostic criteria for BD, and their identification, which reflect the pathophysiological processes of BD, can facilitate the precise diagnosis of the disorder. In this review, the search terms “BD” and “diagnosis” or “biomarker” were used as the key search syntax. In total, 110 studies were included. This review systematically examines the research in the field and summarizes current studies on biomarkers of BD in omics and neuroimaging. We hope that this review will benefit research aimed at establishing objective diagnostic criteria for BD and developing novel therapeutic interventions.
Prioritization of potential drug targets for diabetic kidney disease using integrative omics data mining and causal inference
Junyu Zhang, Jie Peng, Chaolun Yu, Yu Ning, Wenhui Lin, Mingxing Ni, Qiang Xie, Chuan Yang, Huiying Liang, Miao Lin
, Available online  , doi: 10.1016/j.jpha.2025.101265
Abstract(173) HTML Full Text PDF(14)
Abstract:
Diabetic kidney disease (DKD) with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression. Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials. In this study, we integrated large-scale plasma proteomics, genetic-driven causal inference, and experimental validation to identify prioritized targets for DKD using the UK Biobank and FinnGen cohorts. Among 2,844 diabetic patients (528 with DKD), we identified 37 targets significantly associated with incident DKD, supported by both observational and causal evidence. Of these, 22% (8/37) of the potential targets are currently under investigation for DKD or other diseases. Our prospective study confirmed that higher levels of three prioritized targets—insulin-like growth factor binding protein 4 (IGFBP4), family with sequence similarity 3 member C (FAM3C), and prostaglandin D2 synthase (PTGDS)—were associated with a 4.35, 3.51, and 3.57-fold increased likelihood of developing DKD, respectively. In addition, population-level protein-altering variants (PAVs) analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD, through the classic NLRP3- Caspase-1-GSDMD apoptotic axis. Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.
The role of genetics and epigenetics in breast cancer: A comprehensive review of metastasis, risk factors, and future perspectives
Yimeng Chai, Yao Shi
, Available online  , doi: 10.1016/j.jpha.2025.101268
Abstract(63) HTML Full Text PDF(6)
Abstract:
This literature review investigates the mechanisms of resistance to human epidermal growth factor receptor 2 (HER2)-targeted therapies in HER2+ breast cancer, a subtype that accounts for approximately 20% of breast cancer cases. Despite the effectiveness of treatments such as trastuzumab and lapatinib, many patients experience either primary or acquired resistance, leading to treatment failure. The review systematically categorizes various resistance mechanisms, including the role of receptor activator of nuclear factor kappaΒ (RANK) expression, which has been shown to activate the nuclear factor kappaB (NF-κB) pathway, promoting cell survival and contributing to resistance. Other mechanisms include the activation of alternative signaling pathways, such as the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) pathway, and the involvement of tumor-associated fibroblasts, which can drive resistance through receptor tyrosine kinase (RTK) activation. Additionally, the review highlights the importance of understanding these mechanisms to inform the development of novel therapeutic strategies. By identifying potential biomarkers and therapeutic targets, the review suggests that combining HER2 inhibitors with agents that target resistance pathways may enhance treatment efficacy and improve patient outcomes. Overall, this review underscores the complexity of HER2+ breast cancer treatment and the need for continued research to overcome resistance challenges.
Screening of glycan biomarkers for early detection of colorectal cancer based on novel isotope labeling relative quantitative method
Yuxuan Li, Zhenggen Piao, Songze Wang, Longhai Cui, Xinyan Li, Jinlong Ma, Chengqiang Han, Xi-Ling Li, Toufeng Jin, Jun Zhe Min
, Available online  , doi: 10.1016/j.jpha.2025.101262
Abstract(111) HTML Full Text PDF(2)
Abstract:
Colorectal cancer (CRC) is a prevalent gastrointestinal malignancy. However, the lack of diagnostic accuracy of traditional clinical serum biomarkers carcinoembryonic antigen (CEA) and Cancer antigen 19-9 (CA19-9) results in patients being diagnosed at an advanced stage. Herein, we developed a novel method of ultrahigh-performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) for relative quantification based on the nonspecific enzyme pronase E and an isotope mass spectrometry probe d0/d5-BOTC to screen novel glycan biomarkers. We applied the method in a cohort of 102 serum samples (including 51 healthy volunteers (HV), 26 stage II CRC, and 25 stage III CRC) and 90 tissue samples (including 45 paracancerous tissue and 45 cancerous tissue). Results revealed that the serum levels of H5N4F, H5N4F3SA, H4N5F1SA, and H5N4SA2 in CRC patients were significantly different from those in HV (p < 0.01). The area under the curve values of H5N4F, H5N4F3SA, and H4N5F1SA in serum samples were 0.77, 0.71, and 0.91, respectively. The clinical diagnostic accuracies of these glycans ranged from 65% to 91%, which were significantly higher than those of CEA. Additionally, differential glycan profiles in tissues were further examined using the same method and compared with serum levels. H5N4F was found to be significantly down-regulated in all CRC groups (p < 0.0001), indicating strong specificity for CRC diagnosis. The glycans identified in this study are expected to serve as potential biomarkers for the early diagnosis of CRC, offering valuable reference points for clinical diagnosis and treatment.
Comparative two-dimensional NKG2A/CD94 cell membrane chromatography for screening NK cell immune checkpoint inhibitors
Yanting Li, Yanqiu Gu, Weiyue Zhang, Tianhua Li, Chun Chen, Chengliang Wang, Yifeng Chai, Xueqin Ma, Xiaofei Chen
, Available online  , doi: 10.1016/j.jpha.2025.101259
Abstract(190) HTML Full Text PDF(8)
Abstract:
The natural killer (NK) group 2 member A/C-type lectin domain family 4 member A (NKG2A/CD94) heterodimeric receptor is commonly recognized as a crucial immune checkpoint in NK cells. Currently, there is a notable lack of small-molecule inhibitors specifically targeting NKG2A that have progressed to clinical trials, and established screening methodologies for identifying such inhibitors remain limited. Cell membrane chromatography (CMC) is a biochromatographic technique that leverages the specific interactions between membrane receptors and their ligands. In this study, a comprehensive two-dimensional (2D) NKG2A/CD94 and HEK293 CMC comparative analysis system was developed to screen for selective NKG2A/CD94 ligands derived from Echinacea purpurea (L.) Moench and Alpinia katsumadai Hayata. The comprehensive 2D CMC comparative analysis system demonstrated superior selection performance, resulting in the successful screening and identification of five compounds. Of these compounds, chicoric acid and alpinetin exhibited greater binding affinity for the NKG2A/CD94 CMC column compared to the HEK293 CMC column, leading to their selection for further efficacy verification. Surface plasmon resonance (SPR) analysis revealed that chicoric acid and alpinetin exhibit binding affinities of 12.9 and 9.49 μM, to NKG2A/CD94. Molecular docking analyses and pharmacological investigations further demonstrated that both compounds could influence NK cell activation by interacting with the NKG2A/CD94. These findings suggest their potential as novel NKG2A/CD94 immune checkpoint inhibitors. Additionally, the comprehensive 2D CMC system serves as a robust and practical platform for drug discovery, and could be applied to other immune checkpoint receptor models.
Sulfonylation sites for adenine and its nucleosides/nucleotides
Xiaoyue Cheng, Pengcheng Li, Li Xu, Congcong Zhang, Qi Wang, Huiru Tang
, Available online  , doi: 10.1016/j.jpha.2025.101258
Abstract(110) HTML Full Text PDF(1)
Abstract:
Sulfonylation is extensively used to label DNA and RNA, assess their interactions and quantify components including nucleobases and nucleosides/nucleotides although the sulfonylation sites remain controversial. Here, we systematically investigated the sulfonylation of adenine and its nucleosides/nucleotides with 5-(dimethylamino)-naphthalene-1-sulfonyl chloride (DNS-Cl), 5-(diethylamino)-naphthalene-1-sulfonyl chloride (DEANS-Cl), and 5-((N,N-diethylleucyl) amino)-naphthalene-1-sulfonyl chloride (DELANS-Cl). Detailed spectral analysis with nuclear magnetic resonance (NMR) spectroscopy and high-resolution mass spectrometry (HRMS) showed similar sulfonylation behaviors among the reagents. For adenine, its secondary amine in the imidazole ring (N9H) sulfonylated more readily than the exocyclic amino group (N6H2). For adenosine and its nucleotides, the 2'-OH group in the ribosyl moiety was preferably sulfonylated whereas the 3'-OH was the preferred site for 2'-deoxyadenosine and its nucleotides. Alkylation and amidation of the aromatic amino group in these 5-aminonaphthalene-1-sulfonyl chlorides did not influence the sulfonylation preferences. This offered a reliable approach and comprehensive details of such sites for adenine and its nucleosides/nucleotides.
Discovery of anthraquinones as potent Notum inhibitors for treating osteoporosis by integrating biochemical, phytochemical, computational, and experimental assays
Jia Guo, Yuqing Song, Mengru Sun, Jun Qian, Dihang See, Tian Tian, Yunqing Song, Wei Liu, Hongping Deng, Yao Sun, Guangbo Ge, Yongfang Zhao
, Available online  , doi: 10.1016/j.jpha.2025.101256
Abstract(153) HTML Full Text PDF(14)
Abstract:
Osteoporosis, a severe systemic skeletal disorder characterized by decreased bone mineral density, leads to increased risks of bone fragility and fracture. Although some herbal medicines are clinically used for treating osteoporosis, the crucial anti-osteoporotic constituents and their mechanisms have not been well-elucidated. Notum, a negative regulator of Wnt/β-catenin signaling, has been validated as a druggable target for enhancing cortical bone thickness and alleviating osteoporosis. Herein, we showcase an efficient strategy for uncovering the key anti-Notum constituents from herbal medicines via integrating biochemical, phytochemical, computational, and cellular assays. Following screening the anti-Notum potentials of herbal medicines, Polygonum multiflorum Thunb. (PM), a commonly used anti-osteoporosis herb, showed potent and competitive inhibition against Notum. Phytochemical profiling coupling with docking-based virtual screening suggested that three anthraquinones, including rhein, emodin, and chrysophanol, showed high binding-potency towards Notum. Biochemical assays validated that three anthraquinones were strong competitive inhibitors of Notum, while rhein was the most potent one (IC50 = 9.98 nM). Cellular investigations demonstrated that rhein markedly promoted osteoblast differentiation in dexamethasone-challenged MC3T3-E1 osteoblasts, while RNA sequencing showed that rhein remarkably regulated Wnt signaling-related and osteogenic differentiation-related genes. In vivo tests showed that rhein displayed favorable safety profiles in healthy mice and this agent significantly elevated bone mineral density, augmented trabecula and cortical bone thickness in dexamethasone-induced osteoporotic mice. Collectively, this study showcases an efficient strategy for uncovering the key anti-Notum constituents from herbal medicines, while rhein was identified as a naturally occurring Notum inhibitor that shows favorable safety profiles and impressive anti-osteoporosis effects.
LocPro: a deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research
Yintao ZHANG, Lingyan ZHENG, Nanxin YOU, Wei HU, Wanghao JIANG, Mingkun LU, Hangwei XU, Haibin DAI, Tingting FU, Ying ZHOU
, Available online  , doi: 10.1016/j.jpha.2025.101255
Abstract(213) HTML Full Text PDF(4)
Abstract:
Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in ( a ) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expertdriven tool PROFEAT, ( b ) implementing a hybrid deep neural network architecture that integrates CNN, FC, and BiLSTM blocks, and ( c ) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multilabel protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools.
Naringenin: a potential therapeutic agent for modulating angiogenesis and immune response in hepatocellular carcinoma
Wenmei Wu, Xiangyu Qiu, Xiaofan Ye, Zhiliang Zhang, Siguo Xu, Xiuqi Yao, Yinyi Du, Geyan Wu, Rongxin Zhang, Jinrong Zhu
, Available online  , doi: 10.1016/j.jpha.2025.101254
Abstract(165) HTML Full Text PDF(6)
Abstract:
Naringenin (4,5,7-trihydroxyflavonoid) is a naturally occurring bioflavonoid found in citrus fruits, which plays an important role in metabolic syndrome, neurological disorders, cardiovascular diseases. However, the pharmacological mechanism and biological function of naringenin on anti-angiogenesis and anti-tumor immunity have not yet been elucidated. Our study firstly demonstrates that naringenin inhibits the growth of hepatocellular carcinoma (HCC) cells both in vivo and in vitro. naringenin diminishes the ability of HCC cells to induce tube formation and migration of human umbilical vein endothelial cells (HUVECs) and suppresses neovascularization in chorioallantoic membrane assays. Meanwhile, in vivo results demonstrate that naringenin can significantly up-regulating level of CD8+ T cells subsequently increasing the level of immune-related cytokines in the tumor immune microenvironment. Mechanistically, we found that naringenin facilitate the K48-linked ubiquitination and subsequent protein degradation of vascular endothelial growth factor A (VEGFA) and mesenchymal-epithelial transition receptor (c-Met), which reduces the expression of programmed death ligand 1 (PD-L1). Importantly, combination therapy naringenin with PD-L1 antibody or bevacizumab provided better therapeutic effects in liver cancer. Our study reveals that naringenin can effectively inhibit angiogenesis and anti-tumor immunity in liver cancer by degradation of VEGFA and c-Met in a K48-linked ubiquitination manner. This work enlightens the potential effect of naringenin as a promising therapeutic strategy against antiangiogenesis and anti-tumor immunity in HCC.
VLDL: The key factors influencing the distribution of mitotane in patients with adrenocortical carcinoma
Xiangjie Dia, Yixian Liua, Jia You, Yuchun Mena, Zhenlei Wang, Chao Zhou, Ying Jin, Yating Ge, Yongji He, Li Zheng
, Available online  , doi: 10.1016/j.jpha.2025.101252
Abstract(70) HTML Full Text PDF(6)
Abstract:
Integrating explainable deep learning with multi-omics for screening progressive diagnostic biomarkers of hepatocellular carcinoma covering the “inflammation-cancer” transformation
Saiyu Li, Yiwen Zhang, Lifang Guan, Yijing Dong, Mingzhe Zhang, Qian Zhang, Huarong Xu, Wei Xiao, Zhenzhong Wang, Yan Cui, Qing Li
, Available online  , doi: 10.1016/j.jpha.2025.101253
Abstract(108) HTML Full Text PDF(12)
Abstract:
Pathogenesis and Treatment Strategies for Infectious Keratitis: Exploring Antibiotics, Antimicrobial Peptides, Nanotechnology, and Emerging Therapies
Man Yu, Ling Li, Yijun Liu, Ting Wang, Huan Li, Chen Shi, Xiaoxin Guo, Weijia Wu, Chengzi Gan, Mingze Li, Jiaxu Hong, Kai Dong, Bo Gong
, Available online  , doi: 10.1016/j.jpha.2025.101250
Abstract(244) HTML Full Text PDF(12)
Abstract:
Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis. Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.
Understanding the Mechanistic and Therapeutic Perspectives on Cytokines and Chemokines in Acute High-Altitude Illness Syndromes
Amin Ullah, Rajeev K. Singla, Yingbo Zhang, ShanShan Hu, Bairong Shen
, Available online  , doi: 10.1016/j.jpha.2025.101249
Abstract(132) HTML Full Text PDF(0)
Abstract:
Acute high-altitude illnesses (AHAIs), including acute mountain sickness (AMS), high-altitude cerebral edema (HACE), and high-altitude pulmonary edema (HAPE), represent significant health challenges for individuals rapidly ascending to high altitudes. Cytokines (interleukins) and chemokines, which are involved in inflammatory and immunological responses, regulate the response of the body to hypoxic stress. Their dysregulation can contribute to the clinical symptoms of AMS, HACE, and HAPE by increasing vascular permeability, causing edema, and damaging tissue. AHAIs elevate the levels of pro-inflammatory cytokines and chemokines, such as interleukin (IL) 17 (IL-17), tumor necrosis factor α (TNF-α), IL-1, IL-6, C-X-C motif chemokine ligand (CXCL) 10, CXCL8, C-C motif ligand (CCL) 2, and CCL3, exacerbating symptoms. Thus, this review focuses on the cytokines and chemokines involved in AHAIs and the molecular mechanisms that extend beyond these cytokines and chemokines in clinical and preclinical contexts. Identifying these mediators and pathways helps researchers design drugs that reduce symptoms, slow disease progression, and enhance outcomes. Cytokines and chemokines have complex functions in these disorders and may serve as prospective therapeutic targets. Finally, we discuss treatment possibilities for AHAIs (drugs, exercise, and other inhibitors). This knowledge will help us to protect and improve the health of individuals at high altitudes.
Prrx1 promotes mesangial cell proliferation and kidney fibrosis through YAP in diabetic nephropathy
Liu Xu, Jiasen Shi, Huan Li, Yunfei Liu, Jingyi Wang, Xizhi Li, Dongxue Ren, Sijie Liu, Heng Wang, Yinfei Lu, Jinfang Song, Lei Du, Qian Lu, Xiaoxing Yin
, Available online  , doi: 10.1016/j.jpha.2025.101247
Abstract(158) HTML Full Text PDF(5)
Abstract:
Mesangial cell proliferation is an early pathological indicator of diabetic nephropathy (DN). Growing evidence highlights the pivotal role of paired-related homeobox 1 (Prrx1), a key regulator of cellular proliferation and tissue differentiation, in various disease pathogenesis. Notably, Prrx1 is highly expressed in mesangial cells under DN conditions. Both in vitro and in vivo studies have demonstrated that Prrx1 overexpression promotes mesangial cell proliferation and contributes to renal fibrosis in db/m mice. Conversely, Prrx1 knockdown markedly suppresses hyperglycemia-induced mesangial cell proliferation and mitigates renal fibrosis in db/db mice. Mechanistically, Prrx1 directly interacts with the Yes-associated protein 1 (YAP) promoter, leading to the upregulation of YAP expression. This upregulation promotes mesangial cell proliferation and exacerbates renal fibrosis. These findings emphasize the crucial role of Prrx1 upregulation in high glucose-induced mesangial cell proliferation, ultimately leading to renal fibrosis in DN. Therefore, targeting Prrx1 to downregulate its expression presents a promising therapeutic strategy for treating renal fibrosis associated with DN.
The future of pharmaceuticals: Artificial intelligence in drug discovery and development
Chen Fu, Qiuchen Chen
, Available online  , doi: 10.1016/j.jpha.2025.101248
Abstract(498) HTML Full Text PDF(39)
Abstract:
Artificial Intelligence (AI) is revolutionizing traditional drug discovery and development models by seamlessly integrating data, computational power, and algorithms. This synergy enhances the efficiency, accuracy, and success rates of drug research, shortens development timelines, and reduces costs. Coupled with machine learning (ML) and deep learning (DL), AI has demonstrated significant advancements across various domains, including drug characterization, target discovery and validation, small molecule drug design, and the acceleration of clinical trials. Through molecular generation techniques, AI facilitates the creation of novel drug molecules, predicting their properties and activities, while virtual screening optimizes drug candidates. Additionally, AI enhances clinical trial efficiency by predicting outcomes, designing trials, and enabling drug repositioning. However, AI's application in drug development faces challenges, including the need for robust data-sharing mechanisms and the establishment of more comprehensive intellectual property protections for algorithms. AI-driven pharmaceutical companies must also integrate biological sciences and algorithms effectively, ensuring the successful fusion of wet and dry laboratory experiments. Despite these challenges, the potential of AI in drug development remains undeniable. As AI technology evolves and these barriers are addressed, AI-driven therapeutics are poised for a broader and more impactful future in the pharmaceutical industry.
Ginsenoside CK potentiates SIRT1 to alleviate lupus nephritis through compensating for XBP1-mediated endoplasmic reticulum stress in plasma cells
Ziyu Song, Ying Li, Sumei Xu, Shuowen Qian, Wangda Xu, Li Xu, Fengyuan Tian
, Available online  , doi: 10.1016/j.jpha.2025.101245
Abstract(116) HTML Full Text PDF(3)
Abstract:
Immune complex deposition is a critical factor in early renal damage associated with lupus nephritis (LN), and targeting plasma cell aggregation offers a promising therapeutic strategy. Ginsenoside compound K (i.e., 20-O-β-D-glucopyranosyl-20(S)-protopanaxadiol) (CK), a derivative of ginsenoside, has indicated significant potential in alleviating renal damage in lupus-prone mice, potentially by modulating B cell dynamics in response to endoplasmic reticulum (ER) stress. In this study, CK (20 or 40 mg/kg) was orally administered to female MRL/lpr mice for 10 weeks. The effects of CK on B cell subpopulations, renal function, and histopathological changes were evaluated. Single-cell ribonucleic acid sequencing was employed to analyze gene expression profile and pseudotime trajectories during B cell-mediated renal injury. Additionally, in vitro B cell assays were conducted to explore the role of the sirtuin-1 (SIRT1)-X-box binding protein 1 (XBP1) axis in ER stress. Our findings demonstrated that CK effectively reduced anti-dsDNA antibody levels, alleviated systemic inflammation, improved renal function, and facilitated the clearance of deposited immune complexes. CK likely suppressed the unfolded protein response (UPR), delaying the differentiation of renal-activated B cells into plasma cells. It promoted B cell-specific SIRT1 activation and inhibited the splicing of XBP1 into its active form, XBP1s. CK also restored ER morphology by interacting with calmodulin to maintain ER calcium storage, reinforcing SIRT1 functional integrity and promoting XBP1 deacetylation, thereby limiting plasma cell differentiation. In conclusion, CK mitigates plasma cell accumulation in the renal microenvironment by preventing SIRT1-mediated XBP1 splicing, offering a potential therapeutic approach for LN.
Novel hormone therapies for advanced prostate cancer: understanding and countering drug resistance
Zhipeng Wang, Jie Wang, Dengxiong Li, Ruicheng Wu, Jianlin Huang, Luxia Ye, Zhouting Tuo, Qingxin Yu, Fanglin Shao, Dilinaer Wusiman, William C. Cho, Siang Boon Koh, Wei Xiong, Dechao Feng
, Available online  , doi: 10.1016/j.jpha.2025.101232
Abstract(250) HTML Full Text PDF(10)
Abstract:
Prostate cancer is the most prevalent malignant tumor among men, ranking first in incidence and second in mortality globally. Novel hormone therapies (NHT) targeting the androgen receptor (AR) pathway have become the standard of care for metastatic prostate cancer. This review offers a comprehensive overview of NHT, including abiraterone, enzalutamide, apalutamide, darolutamide, and rezvilutamide, which have demonstrated efficacy in delaying disease progression and improving patient survival and quality of life. Nevertheless, resistance to NHT remains a critical challenge. The mechanisms underlying resistance are complex, involving AR gene amplification, mutations, splice variants, increased intratumoral androgens, and AR-independent pathways such as the glucocorticoid receptor, neuroendocrine differentiation, DNA repair defects, autophagy, immune evasion, and activation of alternative signaling pathways. This review discusses these resistance mechanisms and examines strategies to counteract them, including sequential treatment with novel AR-targeted drugs, chemotherapy, poly ADP-ribose polymerase inhibitors, radionuclide therapy, bipolar androgen therapy, and approaches targeting specific resistance pathways. Future research should prioritize elucidating the molecular basis of NHT resistance, optimizing existing therapeutic strategies, and developing more effective combination regimens. Additionally, advanced sequencing technologies and resistance research models should be leveraged to identify novel therapeutic targets and improve drug delivery efficiencies. These advancements hold the potential to overcome NHT resistance and significantly enhance the management and prognosis of patients with advanced prostate cancer.
Trace Fishing Strategy Based on Offline Two-Dimensional Liquid Chromatography Combined PRDX3-Surface Plasmon Resonance for Uncaria Alkaloids
Hui Ni, Zijia Zhang, Ye Lu, Yaowen Liu, Yang Zhou, Wenyong Wu, Xinqin Kong, Liling Shen, Sihan Chen, Huali Long, Cheng Luo, Hao Zhang, Jinjun Hou, Wanying Wu
, Available online  , doi: 10.1016/j.jpha.2025.101244
Abstract(136) HTML Full Text PDF(21)
Abstract:
The rapid screening of bioactive constituents within traditional Chinese medicine (TCM) presents a significant challenge to researchers. Prevailing strategies for the screening of active components in TCM often overlook trace components owing to their concealment by more abundant constituents. To address this limitation, a fishing strategy based on offline two-dimensional liquid chromatography (2D-LC) combined with surface plasmon resonance (SPR) was utilized to screen bioactive trace components targeting peroxiredoxin 3 (PRDX3), using Uncaria alkaloids as a case study. Initially, an orthogonal preparative offline 2D-LC system combining a positively charged C18 column and a conventional C18 column under disparate mobile phase conditions was constructed. To fully reveal the trace alkaloids, thirteen 2D fractions of Uncaria alkaloids were prepared, and their components were characterized using mass spectrometry. Subsequently, employing PRDX3 as the targeting protein, a SPR-based screening approach was established and rigorously validated with geissoschizine methyl ether serving as a positive control for binding. Employing this refined strategy, 29 candidate binding alkaloids were fished from the thirteen 2D fractions. Notably, combining offline 2D-LC with SPR increased the yield of candidate binding components from 10 to 29 when compared to SPR-based screening alone. Subsequent binding affinity assays confirmed that PRDX3 was a direct binding target for the 12 fished alkaloids, with isovallesiachotamine, corynoxeine N-oxide, and cadambine demonstrating the highest affinity for PRDX3. Their interactions were further validated through molecular docking analysis. Subsequent intracellular H2O2 measurement assays and transfection experiments confirmed that these three trace alkaloids enhanced PRDX3-mediated H2O2 clearance. In conclusion, this study introduced an innovative strategy for the identification of active trace components in TCM. This approach holds promise for accelerating research on medicinal components within this field.
Research Progress and Challenges of Molecular Recognition Techniques in the Screening of Active Ingredients in Traditional Chinese Medicine
Lin Li, Qi Li, Yanxiao Li, Dandan Gong, Bonian Zhao
, Available online  , doi: 10.1016/j.jpha.2025.101243
Abstract(116) HTML Full Text PDF(8)
Abstract:
Traditional Chinese medicine (TCM) has become an important treasure trove of natural resources for the development of new medicines due to their diverse compositions, significant therapeutic effects, and few side effects. The screening of active ingredients in TCM represents a crucial step in elucidating the material basis and mechanism of action of TCM. At present, efficient and precise molecular recognition techniques based on intermolecular interactions have been extensively employed for the identification of active ingredients in TCM. This paper presents a review of the fundamental principles underlying solution-phase/affinity ligand fishing, solid-phase/affinity ligand fishing, molecular imprinting and molecular docking techniques, with a particular focus on their applications in the screening of active ingredients in TCM. Furthermore, the paper compares the advantages and disadvantages of the various techniques and identifies the limitations of existing techniques. In conclusion, the paper identifies the prospective trajectory of molecular recognition techniques in the domain of TCM research. This paper not only provides theoretical references for the development of new methods of active ingredient screening but also helps to promote the modernization and internationalization of TCM.
Label-free electrochemical aptasensing of cardiac cell secretomes in cell culture media for the evaluation of drug-induced myocardial injury
Zelin Yang, Xilin Chen, Mingang Liao, Feng Liao, Wen Chen, Qian Shao, Bing Liu, Duanping Sun
, Available online  , doi: 10.1016/j.jpha.2025.101234
Abstract(162) HTML Full Text PDF(7)
Abstract:
Cardiac troponin I (cTnI), a widely used biomarker for assessing cardiovascular risk, can provide a window for the evaluation of drug-induced myocardial injury. Label-free biosensors are promising candidates for detecting cell secretomes, since they do not require labor-intensive processes. In this work, a label-free electrochemical aptasensor is developed for in situ monitoring of cardiac cell secretomes in cell culture media based on target-induced strand displacement. The aptasensing system contains an aptamer-functionalized signal nanoprobe facing trimetallic metal-organic framework nanosheets and a gold nanoparticle-based detection working electrode modified with DNA nanotetrahedron-based complementary DNA for indirect target detection. The signal nanoprobes (termed CAHA) consisted of copper-based metal-organic frameworks, AuPt nanoparticles, horseradish peroxidase, and an aptamer. When the aptasensor is exposed to cardiac cell secretomes, cTnI competitively binds to the aptamer, resulting in the release of signal nanoprobes from the biorecognition interface and electrochemical signal changes. The aptasensor exhibited rapid response times, a low detection limit of 0.31 pg mL-1, and a wide linear range of 0.001-100 ng mL-1. We successfully used this aptasensor to measure cTnI concentrations among secreted cardiac markers during antitumor drug treatment. In general, aptasensors can be used to monitor a variety of cardiac biomarkers in the evaluation of cardiotoxicity.
The latest progress of personalized drug screening and therapy research for clinical highly lethal tumors through the PDX model platform
Yitong Yuan, Hongling Gao, Yanhong Li, Xiangying Jiao
, Available online  , doi: 10.1016/j.jpha.2025.101225
Abstract(160) HTML Full Text PDF(3)
Abstract:
The establishment of mouse models is critical for discovering the biological targets of tumorigenesis and cancer development, preclinical trials of targeted drugs, and formulation of personalized therapeutic regimens. Currently, the patient-derived xenograft (PDX) model is considered a reliable animal tumor model because of its ability to retain the characteristics of the primary tumor at the histopathological, molecular, and genetic levels, and to preserve the tumor microenvironment. The application of the PDX model has promoted in-depth research on tumors in recent years, focusing on drug development, tumor target discovery, and precise treatment of patients. However, there are still some common questions. This review introduces the latest research progress and common questions regarding tumors with high mortality rates, focusing on their application in targeted drug screening and the formulation of personalized medical strategies. The challenges faced, improvement methods, and future development of the PDX model in tumor treatment applications are also discussed. This article provides technical guidance and comprehensive expectations for anti-cancer drug screening and clinical personalized therapy.
Artificial intelligence-aided endoscopic in-line particle size analysis during the pellet layering process
Orsolya Péterfi, Nikolett Kállai-Szabó, Kincső Renáta Demeter, Ádám Tibor Barna, István Antal, Edina Szabó, Emese Sipos, Zsombor Kristóf Nagy, Dorián László Galata
, Available online  , doi: 10.1016/j.jpha.2025.101227
Abstract(96) HTML Full Text PDF(1)
Abstract:
In this study, an artificial intelligence-based machine vision system was developed for in-line particle size analysis during the pellet layering process. Drug-layered pellets were produced by coating microcrystalline cellulose cores with an ibuprofen-containing layering liquid until the target drug content was achieved. Drug content increases with pellet size; therefore, particle size monitoring can ensure product safety and quality. The direct imaging system, consisting of a rigid endoscope, a light source, and a high-speed camera, provides real-time information about pellet size and layer uniformity, enabling timely intervention in the case of out-of-spec products. A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus, ensuring that pellet size could be accurately determined despite the dense flow of the particles. After training the model, the performance of the developed system was assessed by analysing the particle size distribution of pellet cores with variable sizes within the 250–850 μm size range. The endoscopic system was tested in-line at a larger scale during the drug layering of inert pellet cores. The particle size data acquired in real time with the endoscopic imaging system corresponded with the reference methods, demonstrating the feasibility of the proposed machine vision-based method as a process analytical technology tool for in-line process monitoring.
A cascade reaction nanoplatform with magnetic resonance imaging capability for combined photothermal/chemodynamic/gas cancer therapy
Jinyu Wang, Yuhao Guo, Xiaomei Wu, Yiming Ma, Qianqian Qiao, Linwei Li, Tao Liao, Ying Kuang, Cao Li
, Available online  , doi: 10.1016/j.jpha.2025.101223
Abstract(95) HTML Full Text PDF(0)
Abstract:
To effectively exploit the tumor microenvironment (TME), TME-responsive nanocarriers based on cascade reactions have received much attention. In this study, we designed a novel nanoparticle PB@SiO2@MnO2@P-Arg (PMP) to construct a cascade reaction nanoplatform. While using biosafety Prussian blue (PB) for photothermal therapy (PTT), this nanoplatform uses silica (SiO2) as an intermediate layer to assemble Prussian blue and manganese dioxide (MnO2) into a core-shell structure, which effectively enhances the response of the nanoplatform to TME and promotes the effect of chemodynamic therapy (CDT) resulting from glutathione (GSH) depletion and Fenton-like reaction. The released Mn2+ can also be used for magnetic resonance imaging (MRI). Through the cascade reaction, poly-L-arginine (P-Arg) coated on the surface of the nanoparticles can react with hydroxyl radical (·OH) obtained from the Fenton-like reaction to release nitric oxide (NO), which further reacts with O2·- to produce the more toxic peroxynitrite anion (ONOO-). The photothermal effect of PB further enhances the effect of the cascade reaction while reducing the amount of heat required for treatment. In vitro and in vivo studies confirmed the antitumor effects of cascade reaction-based nanoplatforms in combined photothermal/chemodynamic/gas cancer therapies, providing new strategies for the design and fabrication of multifunctional nanoplatforms that integrate diagnostic and therapeutic functions, as well as the application of cascade reactions in multimodal synergistic therapy.
Integrating biogravimetric analysis and machine learning for systematic studies of botanical materials: From bioactive constituent identification to production area prediction
Sinan Wang, Huiru Xiang, Xinyuan Pan, Jianyang Pan, Lu Zhao, Yi Wang, Shaoqing Cui, Yu Tang
, Available online  , doi: 10.1016/j.jpha.2025.101222
Abstract(121) HTML Full Text PDF(7)
Abstract:
In general, bioassay-guided fractionation and isolation of bioactive constituents from botanical materials frequently ended up with the reward of a single compound. However, botanical materials typically exert their therapeutic actions through multi- pathway effects due to the intrinsic complex nature of chemical constituents. In addition, the content of bioactive compounds in botanical materials is largely dependent on humidity, temperature, soil, especially geographical origins, from which rapid and accurate identification of plant materials is pressingly needed. These long-standing obstacles collectively impede the deep exploitation and application of these versatile natural sources. To address the challenges, a new paradigm integrating biogravimetric analyses and machine learning-driven origin classification (BAMLOC) was developed. The biogravimetric analyses are based on absolute qHNMR quantification and in vivo zebrafish model-assisted activity index calculation, by which bioactive substance groups jointly responsible for the bioactivities in all fractions are pinpointed before any isolation effort. To differentiate origin-different botanical materials varying in the content of bioactive substance groups, principal component analysis, linear discriminant analysis, and hierarchical cluster analysis in conjunction with supervised support vector machine are employed to classify and predict production areas based on the detection of volatile organic compounds by E-nose and GC-MS. Expanding BAMLOC to Codonopsis Radix enables the identification of polyacetylenes and pyrrolidine alkaloids as the bioactive substance group for immune restoration effect and accurately determines the origins of plants. This study advances the toolbox for the discovery of bioactive compounds from complex mixtures and lays a more definitive foundation for the in-depth utilization of botanical materials.
Uncovering the covalent inhibitors of SARS-CoV-2 Mpro in Tibetan edible herb Rhodiola crenulata and their synergistic anti-Mpro mechanism
Guang-Hao Zhu, Ya-Ni Zhang, Yuan Xiong, Xu-Dong Hou, Qing-Guang Zhang, Zhao-Qin Zhang, Xiao-Yu Zhuang, Wei-Dong Zhang, Guang-Bo Ge
, Available online  , doi: 10.1016/j.jpha.2025.101224
Abstract(84) HTML Full Text PDF(11)
Abstract:
The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) has been validated as a therapeutic target for antiviral drug development, given its critical role in the viral life cycle. SARS-CoV-2 Mpro contains 12 cysteine residues, which are susceptible to covalent modification by nucleophilic entities. In this study, we showcase an efficient strategy to uncover the key covalent inhibitors of SARS-CoV- 2 Mpro from herbal extracts and decipher their synergistic anti-Mpro mechanisms. Preliminary screening identified Rhodiola crenulata root (RCR), a well-known Tibetan herb, showing the most potent time-dependent inhibition against SARS-CoV-2 Mpro. By integrating fluorescence resonance energy transfer (FRET)-based biochemical assay with phytochemical and chemoproteomic profiling, we efficiently identified thirteen Mpro covalent inhibitors from the crude extract of RCR. Among these, rhodiosin and gallic acid were validated as the key anti-Mpro constituents, due to their strong anti-Mpro effects and high abundance in RCR. Remarkably, their combination exhibited a pronounced synergy in Mpro inhibition. Further intact protein mass measurements and top-down mass spectrometry (MS) analysis, complemented by biophysical methods, elucidated how these two compounds work in concert. Our findings revealed that rhodiosin functions as an allosteric inhibitor, disrupting Mpro dimerization and significantly facilitating the covalent modification of Mpro by gallic acid. Collectively, the covalent SARS-CoV-2 Mpro inhibitors are efficiently identified from a Tibetan herb, while a phytochemical combination with synergistic anti-Mpro effects and their unique allosteric-induced cooperative modification mechanism are revealed.
ZFP36 promotes ferroptosis and mitochondrial dysfunction and inhibits malignant progression in osteosarcoma by regulating the E2F1/ATF4 axis
Shiyue Qin, Hongyang Kong, Lei Jiang
, Available online  , doi: 10.1016/j.jpha.2025.101228
Abstract(111) HTML Full Text PDF(6)
Abstract:
Zinc finger protein 36 (ZFP36) was found to be downregulated in osteosarcoma (OS) tumor tissues. We aimed to investigate the roles and mechanisms of ZFP36 in ferroptosis regulation during OS development. Two Gene Expression Omnibus (GEO) datasets showed that ZFP36 was a differentially expressed gene in OS. Western blot and immunohistochemistry results showed that ZFP36 was downregulated in OS tumors and cell lines. ZFP36 overexpression plasmids and small interfering RNAs were respectively transfected into OS cells. ZFP36 overexpression restrained proliferation, migration, and invasion in MG63 and U2OS cells, while ZFP36 knockdown displayed the opposite results. Moreover, ZFP36 overexpression increased the levels of intracellular Fe2+, reactive oxygen species (ROS), and malondialdehyde (MDA), and decreased the levels of glutathione (GSH), glutathione peroxidase 4 (GPX4), and solute carrier family 7 member 11 (SLC7A11). ZFP36 overexpression disturbed mitochondrial membrane potential (MMP) and mitochondrial morphology in OS cells. However, ZFP36 knockdown had the opposite results. Mechanistic studies indicated that ZFP36 promoted E2F1 messenger RNA (mRNA) degradation by binding to the AU-rich elements (AREs) within E2F1 3' untranslated region (3'UTR) in OS cells. E2F1 overexpression abrogated the effects of ZFP36 overexpression on malignant progression, ferroptosis, and mitochondrial dysfunction in OS cells. Furthermore, E2F1 promoted the transcription activation of activating transcription factor 4 (ATF4) by binding to ATF4 promoter. E2F1 knockdown inhibited malignant progression, and promoted ferroptosis and mitochondrial dysfunction in OS cells, which was abrogated by ATF4 overexpression. Additionally, MG63 cells transfected with lentivirus ZFP36 overexpression vector were injected into nude mice and tumor growth was monitored. ZFP36 overexpression significantly suppressed OS tumor growth under in vivo settings. In conclusion, ZFP36 overexpression promoted ferroptosis and mitochondrial dysfunction and inhibited malignant progression in OS by regulating the E2F1/ATF4 axis. We may provide the promising ZFP36 target for OS treatment.
Caffeic acid alleviates myocardial ischemia-reperfusion injury by directly targeting Keap1N532/M550 and promoting its degradation
Ying Zhang, Huan Lan, Wenjuan Zhai, Lin Jiang, Xiaotong Xia, Fang liu, Lin Zhang, Jinjun Wu, Zhongqiu Liu, Caiyan Wang
, Available online  , doi: 10.1016/j.jpha.2025.101219
Abstract(200) HTML Full Text PDF(20)
Abstract:
Myocardial infarction (MI) is the leading cause of cardiovascular disease-related death worldwide. Nonetheless, existing therapeutic approaches for MI are hampered by issues such as reliance on pharmacological agents and suboptimal patient adherence. Caffeic acid (CA) is a bioactive polyphenolic compound with important anti-inflammatory, anti-bacterial and anti-oxidant functions. Still, its specific role and mechanism in ttreating cardiovascular disease remain to be further studied. In recent years, a large number of studies have shown that the Keap1/Nrf2 pathway is a key factor in the occurrence and development of cardiovascular diseases. In this study, H2O2-induced oxidative stress model of H9c2 cells and left anterior descending branch (LAD) conjunctival induced acute myocardial infarction reperfusion (AMI/R) model were used to evaluate the protective effect of CA on the heart. The interaction between CA and Keap1 was analyzed by CA-labeled fluorescence probe, target fishing, isothermal calorimetry (ITC), protein crystallography and surface plasmon resonance (SPR). Our results suggested that CA binds Keap1 and degrades Keap1 in a p62-dependent manner, further promoting nuclear transcription of Nrf2 and thus effectively reducing oxidative stress. In addition, based on the three-dimensional eutectic structure, it was confirmed that CA directly targets Keap1 protein by interacting with residues M550 and N532, inducing conformation changes in Keap1 protein. We also found that the CA analog chlorogenic acid (GCA) can bind Keap1. In conclusion, this study elucidates a novel molecular mechanism and structural basis for the protective effects of CA against oxidative damage via the Keap1-Nrf2 pathway.
Unveiling the "Dark Matter" of Platelet Involvement in Tumor Microenvironment
Peiyin Zhang, Ruiling Zu, Xingmei Zhang, Hanxiao Ren, Lubei Rao, Dongsheng Wang, Tian Li, Ping Leng, Huaichao Luo
, Available online  , doi: 10.1016/j.jpha.2025.101218
Abstract(116) HTML Full Text PDF(1)
Abstract:
Platelets are well-known for their functions in blood clotting and vascular repair. However, in recent years, the regulatory role of platelets in the occurrence and development of malignant tumors has received significant attention. While extensive research has been conducted on the regulation of tumors by circulating platelets in peripheral blood, there is a lack of coherence and continuity among these studies. The tumor microenvironment encompasses the intricate network of cellular and acellular elements that surround and interact with tumor cells, creating a supportive ecosystem for their survival and growth. It plays a crucial role in the initiation and progression of tumors. Similar to dark matter in the universe, platelets, as tiny and enigmatic entities, play an essential role in tumor development and treatment within the tumor microenvironment. Although our current understanding of platelet regulation in the tumor microenvironment is limited, they hold immense untapped potential. In-depth studies on the tumor microenvironment have revealed platelets as a meaningful component, influencing various aspects of tumor development, metastasis, and immune evasion. Platelets, through the release of various bioactive substances or direct interaction with tumor cells, impact tumor progression while being influenced by the tumor in return. Therefore, understanding the role and mechanisms of platelets in the tumor microenvironment is of great importance for tumor prevention and treatment. This review provides a summary of the research progress on the interplay between platelets and tumors in the tumor microenvironment, and presents a promising outlook on the potential of platelets in tumor therapy.
Real-time monitoring and in vivo visualization of acetylcholinesterase activity with a near-infrared fluorescent probe
Keyun Zeng, Fang Fan, Yuqi Tang, Xiaoyu Wang, Diya Lv, Jieman Lin, Yuxin Zhang, Yingying Zhu, Yifeng Chai, Xiaofei Chen, Quan Li
, Available online  , doi: 10.1016/j.jpha.2025.101204
Abstract(84) HTML Full Text PDF(3)
Abstract:
Acetylcholinesterase (AChE) plays a crucial role in the activities of the nervous system, and its abnormal function can lead to the occurrence and development of neurodegenerative diseases. Hence, an effective method for real-time monitoring of AChE activity is essential. Very recently, several fluorescence sensors have been developed for the detection of AChE activity, but they are usually imaging in the visible region, relatively small Stokes shifts, or long response times, limiting their application for real-time monitoring in vivo. Inspired by that, a near-infrared (NIR) off-on probe ((E)-4-(2-(4-(dicyanomethylene)-4H-chromen-2-yl)vinyl)phenyl dimethylcarbamate, DCM-N) for AChE monitoring with high selectivity and sensitivity is developed. In the probe DCM-N, a bright near-infrared fluorescence emission at 700 nm can be triggered by AChE through the cleavage of amino ester bond in DCM-N, and the resulting fluorescence exhibits a good linear relationship with AChE activity in the range of 0.2 to 16 U/mL, with a detection limit as low as 0.06 U/mL. For real plasma sample detection, DCM-N demonstrates advantages of accurate detection and fast response compared to the traditional Ellman assay for AChE detection. Moreover, DCM-N can be used for imaging of AChE activity in live cells and tracking of AChE activity in zebrafish models, which is of great significance for medical and physiological research related to AChE. DCM-N possesses several notable features such as light-up NIR emission, fast response, large spectral shifts and strong photostability under physiological conditions. These features enable it to monitor AChE activity both in vivo and in vitro, providing a suitable tool for real-time monitoring and in vivo visualization of AChE activity.
Mechanistic insights into honey-boiled detoxification of ChuanWu: a study on alkaloid transformation and supramolecular aggregation
Yu Zhenga, Nina Wei, Chang Lu, Weidong Li, Xiaobin Jia, Linwei Chen, Rui Chen, Zhipeng Chen
, Available online  , doi: 10.1016/j.jpha.2025.101205
Abstract(161) HTML Full Text PDF(16)
Abstract:
Background : ChuanWu (CW), the dried mother root of Aconitum carmichaelii Debx., is a well-known traditional Chinese medicine (TCM) recognized for its potent efficacy and inherent toxicity. The alkaloid components present in CW are significant contributors to its toxic properties. Both traditional knowledge and modern advancements have facilitated the development of detoxification strategies for CW, which include appropriate processing, rational compatibility, and specialized decoction methods. Among these approaches, honey-boiled CW emerges as a distinctive detoxification technique. However, research on the detoxification mechanism of honey- boiled CW remains limited.
Aim of the study : This study aimed to investigate the detoxification mechanism of honey-boiled CW by examining alkaloid transformation and supramolecular aggregation.
Materials and methods : Honey-boiled CW and water-boiled CW were prepared separately for comparative analysis. Ultra-high-performance liquid chromatography- tandem mass spectrometry （ UHPLC-MS/MS） was employed to analyze CW alkaloids, specifically diester alkaloids (DDAs), monoester alkaloids (MDAs), and non- 18 esterified diterpenoid alkaloids (NDAs). Transmission electron microscopy (TEM) was utilized to observe supramolecular aggregation in the honey-boiled CW decoction, which was subsequently isolated and chemically identified. Assemblies of natural deep eutectic solution (NADES) and monomers nanoparticles were prepared for pharmacokinetic studies after oral administration to rats. In addition, we compared the in vivo absorption differences between water-boiled CW, honey-boiled CW and NADES-boiled CW. The toxicity of various treatments for CW was assessed using the LD50 test, with evaluations of both hepatotoxicity and nephrotoxicity. The safety, as well as the anti-inflammatory and analgesic effects of different treatments of CW medicated serum on RAW264.7 cells, were examined through in vitro experiments. These anti-inflammatory and analgesic effects were then further validated through in vivo experiments conducted on mice. Journal Pre-proof4.
Results : Honey played a significant role in altering the alkaloids in boiled CW by promoting the conversion of highly toxic DDAs to less toxic MDAs and preventing the 3 hydrolysis of MDAs into NDAs. Additionally, the honey-boiled CW facilitated the formation of supramolecular aggregates with a diameter of approximately 250 nm. These aggregates effectively hindered the conversion of MDAs into NDAs by encapsulating them. The encapsulated MDAs within the supramolecular aggregates served as a stable drug delivery system under physiological conditions and demonstrated higher bioavailability compared to free benzoylmesaconine (BMA). Subsequent mouse experiments confirmed that honey-boiled CW significantly increased LD50 of CW while reducing hepatotoxicity and nephrotoxicity. Honey-boiled CW significantly improves cell safety and enhances anti-inflammatory and analgesic effects.
Conclusions : Honey-boiled CW exhibited a potent detoxification mechanism by influencing alkaloid transformation and facilitating the formation of supramolecular aggregates. This finding lays the groundwork for the development of detoxification or synergistic strategies within honey-boiled TCM.
Lipidome atlas of human myometrium reveals distinctive lipid signatures associated with adenomyosis: Combination of high-coverage lipidomics and mass spectrometry imaging
Shuo Liang, Jialin Liu, Maokun Liao, Dandan Liang, Yiyi Gong, Bo Zhang, Nan Zhao, Wei Song, Honghui Shi
, Available online  , doi: 10.1016/j.jpha.2025.101197
Abstract(118) HTML Full Text PDF(14)
Abstract:
Adenomyosis is a common gynecological disease characterized by the invasion of endometrial glands and stroma into the myometrium of uterus, the pathological mechanism of which remains unclear yet. Disturbed lipid metabolism extensively affects abnormal cell proliferation and invasion in various diseases. However, the lipidome signature of human myometrium, which could be crucial in the development of adenomyosis, remains unknown. In this study, we generated the first lipidome profiling of human myometrium using a high-coverage and quantitative lipidomics approach based on ultrahigh-performance liquid chromatography coupled with QqQ- mass spectrometry. A total of 317 lipid species were successfully quantified in the myometrial tissues from women with (n = 38) or without (n = 65) adenomyosis who underwent hysterectomy at Peking Union Medical College Hospital. Up to 83 lipid species showed significant alternations in content between the two groups. These lipid aberrations involved multiple metabolic pathways, and emphasized inflammation, cell migration, and immune dysregulation upon adenomyosis. Moreover, receiver operating characteristic curve analysis found that the combination of five lipid species could accurately distinguished the myometrial samples from women with and without adenomyosis with an area under the curve of 0.906. Desorption electrospray ionization mass spectrometry imaging further underscored the heterogeneous distributions of these lipid markers in the adenomyosis lesion and adjacent myometrial tissue. Collectively, these results extremely improved our understanding on the molecular basis of adenomyosis, and could shed light on developing potential biomarkers and new therapeutic directions for adenomyosis.
The integration of artificial intelligence into traditional Chinese medicine
Yanfeng Hong, Sisi Zhu, Yuhong Liu, Chao Tian, Hongquan Xu, Gongxing Chen, Lin Tao, Tian Xie
, Available online  , doi: 10.1016/j.jpha.2024.101157
Abstract(575) HTML Full Text PDF(36)
Abstract:
Traditional Chinese medicine (TCM) is an ancient medical system distinctive and effective in treating cancer, depression, coronavirus disease 2019 (COVID-19), and other diseases. However, the relatively abstract diagnostic methods of TCM lack objective measurement, and the complex mechanisms of action are difficult to comprehend, which hinders the application and internationalization of TCM. Recently, while breakthroughs have been made in utilizing methods such as network pharmacology and virtual screening for traditional Chinese medicine research, the rise of machine learning (ML) has significantly enhanced their integration with TCM. This article introduces representative methodological cases in quality control, mechanism research, diagnosis, and treatment processes of TCM, revealing the potential applications of ML technology in TCM. Furthermore, the challenges faced by ML in TCM applications are summarized, and future directions are discussed.
RCAN-DDI: Relation-aware Cross Adversarial Network for Drug-Drug Interaction Prediction
Yuanyuan Zhang, Xiaoyu Xu, Baoming Feng, Haoyu Zheng, Ci'ao Zhang, Wentao Xu, Zengqian Deng
, Available online  , doi: 10.1016/j.jpha.2024.101159
Abstract(183) HTML Full Text PDF(8)
Abstract:
Drug-drug interaction (DDI) refers to the interaction between two or more drugs in the body, altering their efficacy or pharmacokinetics. Fully considering and accurately predicting DDI has become an indispensable part of ensuring safe medication for patients. In recent years, many deep learning-based methods have been proposed to predict DDI. However, most existing computational models tend to oversimplify the fusion of drug structural and topological information, often relying on methods such as splicing or weighted summation, which fail to adequately capture the potential complementarity between structural and topological features. This loss of information may lead to models that do not fully leverage these features, thus limiting their performance in DDI prediction. To address these challenges, we propose a Relation-aware Cross Adversarial Network for predicting DDI, named RCAN-DDI, which combines a relationship-aware structure feature learning module and a topological feature learning module based on DDI networks to capture multimodal features of drugs. To explore the correlations and complementarities among different information sources, the cross-adversarial network is introduced to fully integrate features from various modalities, enhancing the predictive performance of the model. The experimental results demonstrate that the RCAN-DDI method outperforms other methods. Even in cases of labeled DDI scarcity, the method exhibits good robustness in the DDI prediction task. Furthermore, the effectiveness of the cross-adversarial module is validated through ablation experiments, demonstrating its superiority in learning multimodal complementary information.
Multi-Scale Information Fusion and Decoupled Representation Learning for Robust Microbe-Disease Interaction Prediction
Wentao Wang, Qiaoying Yan, Qingquan Liao, Xinyuan Jin, Yinyin Gong, Linlin Zhuo, Xiangzheng Fu, Dongsheng Cao
, Available online  , doi: 10.1016/j.jpha.2024.101134
Abstract(167) HTML Full Text PDF(4)
Abstract:
Research indicates that microbe activity within the human body significantly influences health by being closely linked to various diseases. Accurately predicting microbe-disease interactions (MDIs) offers critical insights for disease intervention and pharmaceutical research. Current advanced AI-based technologies automatically generate robust representations of microbes and diseases, enabling effective MDI predictions. However, these models continue to face significant challenges. A major issue is their reliance on complex feature extractors and classifiers, which substantially diminishes the models’ generalizability. To address this, we introduce a novel graph autoencoder framework that utilizes decoupled representation learning and multi-scale information fusion strategies to efficiently infer potential MDIs. Initially, we randomly mask portions of the input microbe-disease graph based on Bernoulli distribution to boost self-supervised training and minimize noise-related performance degradation. Secondly, we employ decoupled representation learning technology, compelling the graph neural network (GNN) to independently learn the weights for each feature subspace, thus enhancing its expressive power. Finally, we implement multi-scale information fusion technology to amalgamate the multi-layer outputs of GNN, reducing information loss due to occlusion. Extensive experiments on public datasets demonstrate that our model significantly surpasses existing top MDI prediction models. This indicates that our model can accurately predict unknown MDIs and is likely to aid in disease discovery and precision pharmaceutical research.
Targeted protein degradation: A promising approach for cancer treatment
Muhammad Zafar Irshad Khan, Adila Nazli, Iffat Naz, Dildar Khan, Ihsan-ul Haq, Jian-Zhong Chen
, Available online  , doi: 10.1016/j.jpha.2023.09.004
Abstract(929) HTML Full Text PDF(21)
Abstract:
Targeted protein degradation (TPD) is a promising approach that has the ability to address disease-causing proteins. Compared to traditional inhibition, proteolysis targeting chimera (PROTAC) technology offers various benefits, including the potential to target mutant and overexpressed proteins along with characteristics to target undruggable proteomes. A significant obstacle to the ongoing effective treatment of malignancies is cancer drug resistance, which is developed frequently by mutated or overexpressed protein targets and causes current remedies to continuously lose their effectiveness. The effective use of PROTACs to degrade targets that have undergone mutations and conferred resistance to first-line cancer therapies has attracted much research attention. To find novel/effective treatments, we analyzed the advancements in PROTACs aimed at cancer resistance and targets. This review provides a description of how PROTAC-based anticancer drugs are currently being developed and how to counter resistance if developed to PROTAC technology. Moreover, modern technologies related to protein degradation, including autophagy-targeting chimeras (AUTAC), lysosome-targeting chimeras (LYTAC), antibody-based PROTAC (AbTAC), Glue-body chimeras (GlueTAC), transcription-factor-targeting chimeras (TRAFTAC), RNA-PROTAC, aptamer-PROTAC, Photo-PROTAC, folate-PROTAC, and in-cell click-formed proteolysis targeting chimeras (CLIPTACs), have been discussed along with their mechanisms of action.
Caenorhabditis elegansdeep lipidome profiling by using integrative mass spectrometry acquisitions reveals significantly altered lipid networks
Nguyen Hoang Anh, Young Cheol Yoon, Young Jin Min, Nguyen Phuoc Long, Cheol Woon Jung, Sun Jo Kim, Suk Won Kim, Eun Goo Lee, Daijie Wang, Xiao Wang, Sung Won Kwon
, Available online  , doi: https://doi.org/10.1016/j.jpha.2022.06.006
Abstract(0) HTML Full Text PDF(18)
Abstract:
Lipidomics coverage improvement is essential for functional lipid and pathway construction. powerful approach to discovering organism lipidome is to combine various data acquisitions, uch as full scan (full MS), data-dependent acquisition (DDA), and data-independent acquisition DIA). Caenorhabditis elegans(C. elegans) is a useful model for discovering toxic-induced etabolism, high-throughput drug screening, and a variety of human disease pathways. To etermine the lipidome of C. elegans and investigate lipid disruption from the molecular to the ystem biology level, we used integrative data acquisition. The methyl-tert-butyl ether method was sed to extract L4 stage C. elegans after exposure to triclosan (TCS), perfluorooctanoic acid, and nanopolystyrene (nPS). Full MS, DDA, and DIA integrations were performed to comprehensively profile the C. elegans lipidome by Q-Exactive Plus mass spectrometry. All annotated lipids were then analyzed using lipid ontology and pathway analysis. We annotated up to 940 lipids from 20 lipid classes involved in various functions and pathways. The biological investigations revealed that when C. elegans were exposed to nPS, lipid droplets were disrupted, whereas plasma membrane-functionalized lipids were likely changed in the TCS treatment group. The nPS treatment caused a significant disruption in lipid storage. Triacylglycerol, glycerophospholipid, and ether class lipids were those primarily hindered by toxicants. Finally, toxicant exposure frequently involves numerous lipid-related pathways, including the PI3K/AKT pathway. In conclusion, an integrative data acquisition strategy was used to characterize the C. elegans lipidome, providing valuable biological insights needed for hypothesis generation and validation.

Copyright © Journal of Pharmaceutical Analysis

E-mail: jpasubmit@126.com;  jpaeditor@xjtu.edu.cn   Tel:+86-029-88960092

Address: Western China Science and Technology Innovation Harbour, Xixian New Area, Xi’an, 712000, China

Email alert RSS

Supported by: Beijing Renhe Information Technology Co. Ltd