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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Adaptive multi-view learning method for enhanced drug repurposing using chemical-induced transcriptional profiles, knowledge graphs, and large language models
Yudong Yan, Yinqi Yang, Zhuohao Tong, Yu Wang, Fan Yang, Zupeng Pan, Chuan Liu, Mingze Bai, Yongfang Xie, Yuefei Li, Kunxian Shu, Yinghong Li
, Available online  , doi: 10.1016/j.jpha.2025.101275
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Drug repurposing offers a promising alternative to traditional drug development and significantly reduces costs and timelines by identifying new therapeutic uses for existing drugs. However, the current approaches often rely on limited data sources and simplistic hypotheses, which restrict their ability to capture the multifaceted nature of biological systems. This study introduces adaptive multi-view learning (AMVL), a novel methodology that integrates chemical-induced transcriptional profiles (CTPs), knowledge graph (KG) embeddings, and large language model (LLM) representations, to enhance drug repurposing predictions. AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning, matrix factorization, and ensemble optimization techniques to integrate heterogeneous multisource data. Comprehensive evaluations on benchmark datasets (Fdataset, Cdataset, and Ydataset) and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art methods, achieving superior accuracy in predicting drug-disease associations across multiple metrics. Literature-based validation further confirmed the model's predictive capabilities, with seven out of the top ten predictions corroborated by post-2011 evidence. To promote transparency and reproducibility, all data and codes used in this study were open-sourced, providing resources for processing CTPs, KG, and LLM-based similarity calculations, along with the complete AMVL algorithm and benchmarking procedures. By unifying diverse data modalities, AMVL offers a robust and scalable solution for accelerating drug discovery, fostering advancements in translational medicine, and integrating multi-omics data. We aim to inspire further innovations in multisource data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.
Combining transformer and 3DCNN models to achieve co-design of structures and sequences of antibodies in a diffusional manner
Yue Hu, Feng Tao, Jiajie Xu, WenJun Lan, Jing Zhang, Wei Lan
, Available online  , doi: 10.1016/j.jpha.2025.101267
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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
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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
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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
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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
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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
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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
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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.
EvoNB: A Protein Language Model-Based Workflow for Nanobody Mutation Prediction and Optimization
Danyang Xiong, Yongfan Ming, Yuting Li, Shuhan Li, Kexin Chen, Jinfeng Liu, Lili Duan, Honglin Li, Min Li, Xiao He
, Available online  , doi: 10.1016/j.jpha.2025.101260
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The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody–antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.
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
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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
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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(33) HTML Full Text PDF(1)
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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
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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(59) HTML Full Text PDF(2)
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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(55) HTML Full Text PDF(2)
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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.
3D-EDiffMG: 3D equivariant diffusion-driven molecular generation to accelerate drug discovery
Chao Xu, Runduo Liu, Yufen Yao, Wanyi Huang, Zhe Li, Hai-Bin Luo
, Available online  , doi: 10.1016/j.jpha.2025.101257
Abstract(61) HTML Full Text PDF(3)
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Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and nonbonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.
Impact of FASN-enriched EVs on endothelial cell function in obstructive sleep apnea hypopnea syndrome
Yuan Tian, Dan Zhang, Huaian Yang, Xiaoli Zhang, Shengqun Xu
, Available online  , doi: 10.1016/j.jpha.2025.101251
Abstract(29) HTML Full Text PDF(2)
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Endothelial dysfunction is a key factor linking obstructive sleep apnea hypopnea syndrome (OSAHS) with cardiovascular diseases. In this study, we used advanced proteomics and metabolomics approaches to investigate the impact of extracellular vesicles (EVs) derived from the serum of OSAHS patients on endothelial function. Our multi-omics analysis identified dysregulated pathways related to fatty acid metabolism, apoptosis regulation, and inflammatory responses, highlighting fatty acid synthase (FASN) as a crucial player in OSAHS-induced endothelial dysfunction. Both in vitro and in vivo experiments demonstrated that FASN-enriched EVs impair endothelial cell viability and disrupt metabolic homeostasis, offering new insights for the development of targeted therapies for cardiovascular complications associated with OSAHS.
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
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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
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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
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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
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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
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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.
E3 ubiquitin ligase FBXW11-mediated downregulation of S100A11 promotes sensitivity to PARP inhibitor in ovarian cancer
Ligang Chen, Mingyi Wang, Yunge Gao, Yanhong Lv, Lianghao Zhai, Jian Dong, Yan Chen, Xia Li, Xin Guo, Biliang Chen, Yi Ru, Xiaohui Lv
, Available online  , doi: 10.1016/j.jpha.2025.101246
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Resistance to poly adenosine diphosphate (ADP)-ribose polymerase inhibitor (PARPi) presents a considerable obstacle in the treatment of ovarian cancer. F-box and tryptophan-aspartic (WD) repeat domain containing 11 (FBXW11) modulates the ubiquitination of growth-and invasion-related factors in lung cancer, colorectal cancer, and osteosarcoma. The function of FBXW11 in PARPi therapy is still ambiguous. In this study, RNA sequencing showed that FBXW11 expression was raised in ovarian cancer cells that had been treated with PARPi. FBXW11 was abnormally expressed at low levels in high-grade serous ovarian cancer (HGSOC) tissues, and low levels of FBXW11 were associated with shorter overall survival and progression-free survival in HGSOC patients. Overexpressing FBXW11 made ovarian cancer more sensitive to PARPi, while knocking down FBXW11 made it less sensitive. The four-dimensional (4D) label-free quantitative proteomic analysis revealed that FBXW11 targeted S100 calcium binding protein A11 (S100A11) and promoted its degradation through ubiquitination. The increased degradation of S100A11 led to less efficient DNA damage repair, which in turn contributed to increased PARPi-induced DNA damage. The role of FBXW11 in promoting PARPi sensitivity was also confirmed in xenograft mouse models. In summary, our study confirms that FBXW11 promotes the susceptibility of ovarian cancer cells to PARPi via affecting S100A11-mediated DNA damage repair.
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(79) HTML Full Text PDF(3)
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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(19) HTML Full Text PDF(1)
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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
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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.
Ginkgolic acid inhibits CD8+ T cell activation and induces ferroptosis by lactate dehydrogenase A to exert immunosuppressive effect
Sai Zhang, Zhuyuan Si, Mingkun Liu, Wenjuan Hao, Tong Xia, Zeyang Liu, Gang Du, Bin Jin
, Available online  , doi: 10.1016/j.jpha.2025.101233
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In the context of the development of transplant oncology, it is of great clinical significance to find a drug with both antitumor and immunosuppressive effects for liver transplantation patients with hepatocellular carcinoma (HCC). The antitumor effect of ginkgolic acid (GA) has been confirmed, and some studies suggest that GA may also have an immunosuppressive effect. The immunosuppressive effect of GA was evaluated by histopathology, T- cell subpopulation, and cytokine detection in rat liver transplantation and mouse cardiac transplantation models, and transcriptomic and metabolomic analysis was used to explore the underlying mechanism of the GA immunosuppressive effect. Metabolites, activation, and ferroptosis markers of CD8+ T cells were detected in vivo and in vitro. Based on rat liver transplantation and mouse cardiac transplantation models, the immunosuppressive effect of GA was first confirmed by histopathology, T-cell subpopulation, and cytokine detection. In the mouse cardiac transplantation model, transcriptomics combined with metabolomics demonstrated for the first time that GA inhibited lactate dehydrogenase A (LDHA) expression and pyruvate metabolism in CD8+ T cells. It was confirmed in vivo and in vitro that GA inhibited pyruvate metabolism of CD8+ T cells through LDHA, inhibiting their activation and inducing ferroptosis. Overexpression of LDHA partially reversed the effect of GA on the metabolism, activation, and ferroptosis of CD8+ T cells in vitro.GA mediates metabolic reprogramming through LDHA to inhibit the activation and induce ferroptosis of CD8+ T cells to exert an immunosuppressive effect, which lays an experimental foundation for the future clinical application of its immunosuppressive effect.
Fingerprint-enhanced hierarchical molecular graph neural networks for property prediction
Shuo Liu, Mengyun Chen, Xiaojun Yao, Huanxiang Liu
, Available online  , doi: 10.1016/j.jpha.2025.101242
Abstract(77) HTML Full Text PDF(3)
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Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials. Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction. However, traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules. Similarly, graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information. To address these limitations, we propose a novel fingerprint-enhanced hierarchical graph neural network (FH-GNN) for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints. The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks (DMPNN) on a hierarchical molecular graph that integrates atomic-level, motif-level, and graph-level information along with their relationships. Additionally, we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features, creating a comprehensive molecular embedding that integrated hierarchical molecular structures with domain knowledge. Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction, validating its capability to comprehensively capture molecular information. By integrating molecular structure and chemical knowledge, FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.
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(34) HTML Full Text PDF(3)
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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(38) HTML Full Text PDF(2)
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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(40) HTML Full Text PDF(3)
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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(60) HTML Full Text PDF(2)
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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(31) HTML Full Text PDF(0)
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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.
Generation of SARS-CoV-2 dual-target candidate inhibitors through 3D equivariant conditional generative neural networks
Zhong-Xing Zhou, Hong-Xing Zhang, Qingchuan Zheng
, Available online  , doi: 10.1016/j.jpha.2025.101229
Abstract(90) HTML Full Text PDF(4)
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SARS-CoV-2 mutations are influenced by random and uncontrollable factors, and the risk of the next 3 widespread epidemic remains. Dual-target drugs that synergistically act on two targets exhibit strong 4 therapeutic effects and advantages against mutations. In this study, a novel computational workflow was 5 developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main 6 protease selected as the two target proteins. The drug-like molecules of our self-constructed 3D scaffold 7 database were used as high-throughput molecular docking probes for feature extraction of two target protein 8 pockets. A multi-layer perceptron (MLP) was employed to embed the binding affinities into a latent space as 9 conditional vectors to control conditional distribution. Utilizing a conditional generative neural network, cG- 10 SchNet, with 3D Euclidean group (E3) symmetries, the conditional probability distributions of molecular 3D 11 structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated. 12 The 1D probability, 2D joint probability, and 2D cumulative probability distribution results indicate that the 13 generated sets are significantly enhanced compared to the training set in the high binding affinity area. 14 Among the 201 generated molecules, 42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol 15 while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol, demonstrating structure diversity 16 along with strong dual-target affinities, good ADMET properties, and ease of synthesis. Dual-target drugs 17 are rare and difficult to find, and our “High-Throughput Docking - Multi-Conditional Generation” workflow 18 offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.
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(41) HTML Full Text PDF(0)
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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(45) HTML Full Text PDF(6)
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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.
Self-assembled and intestine-targeting florfenicol nano-micelles effectively inhibit drug-resistant Salmonella typhimurium, eradicate biofilm, and maintain intestinal homeostasis
Runan Zuo, Linran Fu, Wanjun Pang, Lingqing Kong, Liangyun Weng, Zeyuan Sun, Ruichao Li, Shaoqi Qu, Lin Li
, Available online  , doi: 10.1016/j.jpha.2025.101226
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Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions. Emerging multidrug resistant (MDR) Salmonella typhimurium has raised concern for its effect on pathogenic infection and mortality in humans caused by enteric diseases. To combat these MDR Salmonella typhimurium pathogens, highly effective and broad-spectrum antibiotics such as flufenicol (FFC) need to be evaluated for their potent antibacterial activity against Salmonella typhimurium. However, the low solubility and low oral bioavailability of flufenicol need to be addressed to better combat AMR. In this work, we develop a novel nano-formulation, flufenicol nano-micelles (FTPPM), which are based on D-α-tocopherol polyethylene glycol 1000 succinate (TPGS)/poloxamer 188 (P188), for the targeted treatment of biofilms formed by drug-resistant Salmonella typhimurium in the intestine. Herein, FTPPM were prepared via a thin film hydration method. The preparation process for the mixed micelles is simple and convenient compared with other existing nanodrug delivery systems, which can further decrease production costs. The optimized FTPPM demonstrated outstanding stability and sustained release. An evaluation of the in vivo anti-drug-resistant Salmonella typhimurium efficacy demonstrated that FTPPM showed a stronger efficacy (68.17%) than did florfenicol-loaded TPGS polymer micelles (FTPM), flufenicol active pharmaceutical ingredients (FFC-API), and flufenicol commercially available medicine (FFC-CAM), and also exhibited outstanding biocompatibility. Notably, FTPPM also inhibited drug-resistant Salmonella typhimurium from forming biofilms. More importantly, FTPPM effectively restored intestinal flora disorders induced by drug-resistant Salmonella typhimurium in mice. In summary, FTPPM significantly improved the solubility and oral bioavailability of florfenicol, enhancing its efficacy against drug-resistant Salmonella typhimurium both in vitro and Journal Pre-proof in vivo. FTPPM represent a promising drug-resistant Salmonella typhimurium treatment for curbing bacterial resistance via oral administration.
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
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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(28) HTML Full Text PDF(4)
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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(40) HTML Full Text PDF(1)
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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.
Machine learning-assisted microfluidic approach for broad-spectrum liposome size control
Yujie Jia, Xiao Liang, Li Zhang, Jun Zhang, Hajra Zafar, Shan Huang, Yi Shi, Jian Chen, Qi Shen
, Available online  , doi: 10.1016/j.jpha.2025.101221
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Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.
Disorder of phospholipid metabolism in the renal cortex and medulla contributes to acute tubular necrosis in mice after cantharidin exposure using integrative lipidomics and spatial metabolomics
Tianmu He, Kexin Lin, Lijuan Xiong, Wen Zhang, Huan Zhang, Cancan Duan, Xiaofei Li, Jianyong Zhang
, Available online  , doi: 10.1016/j.jpha.2025.101210
Abstract(35) HTML Full Text PDF(4)
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Cantharidin (CTD), a natural compound used to treat multiple tumors in the clinic setting, has been limited due to acute kidney injury (AKI). However, the major cause of AKI and its underlying mechanism remain to be elucidated. Serum creatinine and blood urea nitrogen (BUN) were detected through pathological evaluation after CTD (1.5 mg/kg) oral gavage in mice in 3 d. Kidney lipidomics based on ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to investigate lipids disorder after CTD exposure in mice. Then, spatial metabolomics based on matrix-assisted laser desorption/ionization mass spectrometry imaging (MSI) was used to detect the kidney spatial distribution of lipids. Integrative analysis was performed to reveal the spatial lipid disorder mechanism and verify key lipids in vitro. The results showed that the levels of serum creatinine and BUN were increased, and tubular necrosis was observed in mouse kidneys, resulting in acute tubular necrosis (ATN) in CTD-induced AKI. Then, lipidomics results revealed that after CTD exposure, 232 differential lipid metabolites and 11 pathways including glycerophospholipid (GP) and sphingolipid (SL) metabolism were disrupted. Spatial metabolomics revealed that 55 spatial differential lipid metabolites and nine metabolic pathways were disturbed. Subsequently, integrative analysis found that GP metabolism was stimulated in the renal cortex and medulla, whereas SL metabolism was inhibited in the renal cortex. Accumulated lysophosphatidylcholine (LysoPC (18:2(9Z,12Z))), LysoPC (16:0/0:0), and glycerophosphocholine and decreased sphingomyelin (SM) (d18:0/16:0), SM (d18:1/24:0) and SM d42:1 were the key toxic lipids. Among them, LysoPC (16:0/0:0) was increased in the CTD group at 1.1196 μg/mL, which aggravated CTD-induced ATN in the Human Kidney-2 cells. Lysophosphatidylcholine acyltransferase was inhibited and choline phosphotransferase 1 was activated after CTD intervention in mice and in the human kidney-2 cells in mice. CTD induces ATN, resulting in AKI, by activating GP metabolism and inhibiting SL metabolism in the renal cortex and medulla, LysoPC (16:0/0:0), Lysophosphatidylcholine acyltransferase, and choline phosphotransferase 1 may be the therapeutic targets.
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
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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
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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.
Silent or low expression of blaTEM and blaSHV suggests potential for targeted proteomics in clinical detection of β-lactamase-related antimicrobial resistance
Huige Wu, Wenting Dong, Xinxin Hu, Chunyang Xie, Xinyi Yang, Congran Li, Guoqing Li, Yun Lu, Xuefu You
, Available online  , doi: 10.1016/j.jpha.2025.101220
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Biological activity analysis of baicalin nanodrugs: Nanosizing enhances antiviral and anti-inflammatory effects in the treatment of viral pneumonia
Chenqi Chang, Chang Lu, Yu Zheng, Lili Lin, XiuZhen Chen, Linwei Chen, Zhipeng Chen, Rui Chen
, Available online  , doi: 10.1016/j.jpha.2025.101201
Abstract(37) HTML Full Text PDF(5)
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Respiratory syncytial virus (RSV) is a ubiquitous respiratory virus that affects individuals of all ages; however, there is a notable lack of targeted treatments. RSV infection is associated with a range of respiratory symptoms, including bronchiolitis and pneumonia. Baicalin (BA) exhibits significant therapeutic effects against RSV infection through mechanisms of viral inhibition and anti-inflammatory action. Nonetheless, the clinical application of BA is constrained by its low solubility and bioavailability. In this study, we prepared BA nanodrugs (NDs) with enhanced water solubility utilizing the supramolecular self-assembled strategy, and we further conducted a comparative analysis of this pharmacological activity between free drugs and NDs of BA. Both in vitro and in vivo results demonstrated that BA NDs significantly enhanced the dual effects of viral inhibition and inflammation relief compared to free BA, attributed to prolonged lung retention, improved cellular uptake, and increased targeting affinity. Our study confirms that the nanosizing strategy, a straightforward approach to enhance drug solubility, can also increase biological activity compared to free drugs with the same content, thereby providing a potential ND for RSV treatment. This correlation analysis between the existing forms of drugs and their biological activity offers a novel perspective for research on the active ingredients of traditional Chinese medicine.
Greenness evaluation metric for analytical methods and software
Tong Xin, Luyao Yu, Wenying Zhang, Yingxia Guo, Chuya Wang, Zhong Li, Jiansong You, Hongyu Xue, Meiyun Shi, Lei Yin
, Available online  , doi: 10.1016/j.jpha.2025.101202
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The focus of green analytical chemistry (GAC) is to minimize the negative impacts of analytical procedures on human safety, human health, and the environment. Several factors, such as the reagents used, sample collection, sample processing, instruments, energy consumed, and the quantities of hazardous materials and waste generated during analytical procedures, need to be considered in the evaluation of the greenness of analytical assays. In this study, we propose a greenness evaluation metric for analytical methods (GEMAM). The new greenness metric is simple, flexible, and comprehensive. The evaluation criteria are based on both the 12 principles of GAC (SIGNIFICANCE) and the 10 factors of sample preparation, and the results are presented on a 0–10 scale. The GEMAM calculation process is easy to perform, and its results are easy to interpret. The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number
pH-responsive biomimetic zeolitic imidazolate framework-based nanoparticles for co-delivery of cetuximab and siRNA in synergistic therapy of laryngeal squamous cell carcinoma
Liyin Wang, Milad Ashrafizadeh, Gautam Sethi, Xinjia Zhou
, Available online  , doi: 10.1016/j.jpha.2025.101203
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Suboptimal treatment of laryngeal squamous cell carcinoma (LSCC) reduces survival rate. The poor bioavailability and resistance to cetuximab (Cet) and the instability of small interfering RNA (siRNA) limit their therapeutic efficacy in LSCC. This study aimed to develop a Cet and focal adhesion kinase (FAK) siRNA (siFAK) co-delivery nanosystem. Zeolitic imidazolate framework-8 (ZIF-8), with its large specific surface area and pH-responsive properties, is an ideal delivery carrier that allows controlled drug release in the acidic tumor microenvironment. Therefore, Cet was loaded onto ZIF-8 and encapsulated in a TU177 cell membrane (TCM) after the electrostatic adsorption of siFAK. Fourier transform infrared (FTIR) spectroscopy, transmission electron microscopy (TEM), scanning electron microscopy (SEM), zeta potential, Xray diffraction, and particle size analyses were used to characterize Cet/siFAK@ZIF- 8@TCM. TU177 cells and subcutaneously transplanted tumor-bearing nude mice were used to evaluate the intracellular uptake, cytotoxicity, in vivo biocompatibility, biodistribution, biosafety, pH responsiveness, and anti-LSCC efficacy of Cet/siFAK@ZIF-8@TCM. After ZIF-8@TCM were loaded with Cet and siFAK, alterations in their physical and crystal structures, particle size, and zeta potential were observed. Meanwhile, the co-delivery system increased the loading of Cet through the electrostatic adsorption of siFAK to Cet-loaded ZIF-8. The intracellular uptake of Cet/siFAK@ZIF-8@TCM also protected siFAK from degradation, effectively reducing the messenger RNA (mRNA) and protein expression levels of FAK in LSCC cells. The ZIF-8@TCM nanosystem for co-delivery of Cet and siFAK exhibited pHresponsiveness and tumor-targeting capabilities, thereby exerting anti-LSCC effects. Co-delivery of Cet and siFAK via the pH-responsive ZIF-8@TCM system enabled the targeted release of the chemotherapeutic and gene, in turn maximizing their anti-LSCC effect while ensuring biosafety.
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(60) HTML Full Text PDF(10)
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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(43) HTML Full Text PDF(4)
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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.
Late-stage labeling of diverse peptides and proteins with iodine-125
Aleš Marek, Břetislav Brož, Michal Kriegelstein, Gabriela Nováková, Jana Hojcsková, Miroslava Blechová, Lenka Žáková, Jiří Jiráček, Lenka Maletínská
, Available online  , doi: 10.1016/j.jpha.2025.101198
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The preparation of specifically 125I-labeled peptides of high purity and specific activity represents a key tool for the detailed characterization of their binding properties in interaction with their binding partners. Early synthetic methods for the incorporation of iodine faced challenges such as harsh reaction conditions, the use of strong oxidants and low reproducibility. Herein, we review well-established radiolabeling strategies available to incorporate radionuclide into a protein of interest, and our long-term experience with a mild, simple and generally applicable technique of iodine-125 late-stage-labeling of biomolecules using the Pierce iodination reagent for the direct solid-phase oxidation of radioactive iodide. General recommendations, tips, and details of optimized chromatographic conditions to isolate pure, specifically 125I-mono-labeled biomolecules are illustrated on a diverse series of (poly)peptides, ranging up to 7.6 kDa and 67 amino acids (aa). These series include peptides that contain at least one tyrosine or histidine residue, along with those featuring disulfide crosslinking or lipophilic derivatization. This mild and straightforward late-stage-labeling technique is easily applicable to longer and more sensitive proteins, as demonstrated in the cases of IGF-BP-3 (the insulin-like growth factor binding protein, 29 kDa, 264 aa) and ALS (the acid-labile subunit, 93 kDa, 578 aa).
Tailoring a traditional Chinese medicine prescription for complex diseases: A novel multi-targets-directed gradient weighting strategy
Zhe Yu, Teng Li, Zhi Zheng, Xiya Yang, Xin Guo, Xindi Zhang, Haoying Jiang, Lin Zhu, Bo Yang, Yang Wang, Jiekun Luo, Xueping Yang, Tao Tang, En Hu
, Available online  , doi: 10.1016/j.jpha.2025.101199
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Traditional Chinese medicine (TCM) exerts integrative effects on complex diseases owing the characteristics of multiple components with multiple targets. However, the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians, which has been a major challenge in the global acceptance and application of TCM. Therefore, a standardized TCM prescription system needs to be explored to promote its clinical application. In this study, we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation. We tested its efficacy against intracerebral hemorrhage (ICH). First, the top 100 ICH targets in the GeneCards database were screened according to their relevance scores. Then, SymMap and Traditional Chinese Medicine Systems Pharmacology (TCMSP) databases were applied to find out the target-related ingredients and ingredient-containing herbs, respectively. The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets. The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions. The absorbed components in the serum were detected. In a mouse model of ICH, the new prescription exerted multifaceted effects, including improved neurological function, as well as attenuated neuronal damage, cell apoptosis, vascular leakage, and neuroinflammation. These effects matched well with the core pathological changes in ICH. The multi-targets- directed gradient-weighting strategy presents a promising avenue for tailoring precise, multipronged, unbiased, and standardized TCM prescriptions for complex diseases. This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts
Identify drug-drug interactions via deep learning: a real world study
Jingyang Li, Yanpeng Zhao, Zhenting Wang, Chunyue Lei, Lianlian Wu, Yixin Zhang, Song He, Xiaochen Bo, Jian Xiao
, Available online  , doi: 10.1016/j.jpha.2025.101194
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Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a multi-dimensional feature fusion model named MDFF, which integrates one-dimensional Simplified Molecular Input Line Entry System sequence features, two- dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real- world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.
Breaking Barriers: MS-BDF Tools in the Quality Control of Insectderived Traditional Chinese Medicine
Caixia Yuan, Dandan Zhang, Hairong Zhang, Jiyang Dong, Caisheng Wu
, Available online  , doi: 10.1016/j.jpha.2025.101193
Abstract(56) HTML Full Text PDF(6)
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Exploring Cellular Plasticity and Resistance Mechanisms in Lung Cancer: Innovations and Emerging Therapies
Caiyu Jiang, Shenglong Xie, Kegang Jia, Gang Feng, Xudong Ren, Youyu Wang
, Available online  , doi: 10.1016/j.jpha.2024.101179
Abstract(35) HTML Full Text PDF(3)
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Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and remains the leading cause of cancer-related mortality worldwide. Firstly, this review explores the limitations of conventional therapies—chemotherapy, radiotherapy, and surgery—focusing on the development of drug resistance and significant toxicity that often hinder their efficacy. Thereafter, advancements in targeted therapies, such as immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), are discussed, highlighting their impact on improving outcomes for patients with specific genetic mutations, including c-ros oncogene 1 receptor tyrosine kinase (ROS1), anaplastic lymphoma kinase (ALK), and epidermal growth factor receptor (EGFR). Additionally, the emergence of novel immunotherapies and phytochemicals is examined, emphasizing their potential to overcome therapeutic resistance, particularly in advanced-stage diseases. The review also delves into the role of next-generation sequencing (NGS) in enabling personalized treatment approaches and explores the clinical potential of innovative agents, such as bispecific T-cell engagers (BiTEs) and antibody-drug conjugates (ADCs). Finally, we address the socioeconomic barriers that limit the accessibility of these therapies in low-resource settings and propose future research directions aimed at improving the long-term efficacy and accessibility of these treatments.
The uric acid lowering potential of bioactive natural products and extracts derived from traditional Chinese medicines: A review and perspective
Yaolei Li, Zhijian Lin, Hongyu Jin, Feng Wei, Shuangcheng Ma, Bing Zhang
, Available online  , doi: 10.1016/j.jpha.2024.101183
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Hyperuricemia (HUA) and gout became typical metabolic disorders characterized by multiple pathogenic factors. Their incidence increased annually, affecting younger populations. Given that uric acid (UA) and inflammation were the primary disease mechanisms, the search for effective and low-side-effect UA-lowering and antiinflammatory drugs became a pressing scientific priority. Traditional Chinese medicine (TCM) encompassed a rich array of theoretical and practical experience, along with a diverse range of chemical substances, making herbs or their components potential sources for therapeutic drugs. Despite the significant role that modern herbal medicines played in treating HUA and gout, the existing research literature remained fragmented, lacking comprehensive and systematic reviews. In this review, we focused on the regulation of UA and summarized the discovery of UA-lowering pharmacodynamic components or ingredients derived from herbs and formulas, as well as their multitargeted mechanisms of action. Emphasizing this focus, we proposed that, compared to acute inflammation, low-grade inflammation may have played a relatively "unnoticed" role in the disease process. In contrast to Western medicine, we discussed the risks and benefits of herbal medicines and their ingredients for treatment, drawing from theoretical insights and clinical practice. This review offered comprehensive perspectives on the research into anti-HUA and gout treatments using herbal medicines and their natural products. Additionally, it provided a forward-looking view on natural product discovery, the exploration of therapeutic strategies, and new drug research in this field.
A Novel Exploration of COL11A1's Role in Regulating Myeloid-Derived Suppressor Cell Activation within the Colon Cancer Microenvironment
Wei Niu, Xiaxia Du, Yang Song, Lianyi Guo, Baohai Liu, Xin Tong
, Available online  , doi: 10.1016/j.jpha.2024.101181
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This study aimed to elucidate the role of collagen type XI alpha 1 (COL11A1)-positive cancer- associated fibroblasts (CAFs) in modifying the tumor microenvironment of colon cancer (CC) and facilitating immune evasion through interactions with myeloid-derived suppressor cells (MDSCs). Using single-cell transcriptomic sequencing, we analyzed the interplay between COL11A1-positive CAFs and MDSCs in the CC microenvironment, focusing on how COL11A1 impacts MDSC differentiation and activation. The results demonstrate that COL11A1 expression in fibroblasts significantly enhances matrix metalloproteinase 3 (MMP3) and matrix metalloprotease 13 (MMP13) expression, leading to paracrine induction of MDSC differentiation and activation, which promotes immune evasion and tumor growth. Additionally, we observed that COL11A1 knockout suppresses tumor growth and hinders immune evasion. These findings underscore the essential role of COL11A1-positive CAFs in establishing an immunosuppressive tumor microenvironment conducive to CC progression. By elucidating the molecular pathway through which COL11A1 influences MDSC activity, this research suggests new therapeutic avenues for targeting the tumor microenvironment in CC, particularly through modulating COL11A1 expression in CAFs.
Effect of cholesterol on distribution, cell uptake, and protein corona of lipid microspheres at sites of cardiovascular inflammatory injury
Lingyan Li, Xingjie Wu, Qianqian Guo, Yu'e Wang, Zhiyong He, Guangqiong Zhang, Shaobo Liu, Liping Shu, Babu Gajendran, Ying Chen, Xiangchun Shen, Ling Tao
, Available online  , doi: 10.1016/j.jpha.2024.101182
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Cholesterol (CH) plays a crucial role in enhancing the membrane stability of drug delivery systems (DDS). However, its association with conditions such as hyperlipidemia often leads to criticism, overshadowing its influence on the biological effects of formulations. In this study, we reevaluated the delivery effect of CH using widely applied lipid microspheres (LM) as a model DDS. We conducted comprehensive investigations into the impact of CH on the distribution, cell uptake, and protein corona (PC) of LM at sites of cardiovascular inflammatory injury. The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage. Then, the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy. Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma expression in vascular endothelial cells and estrogen receptor alpha protein levels in myocardial cells, thereby enhancing LM uptake at cardiovascular inflammation sites. Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with cholesterol metabolismrelated apolipoprotein family members such as apolipoprotein A-V (Apoa5); this may be a major contributing factor to their prolonged circulation in vivo and explains why CH enhances the distribution of LM at cardiovascular inflammatory injury sites. It should be noted that changes in cell types and physiological environments can also influence the biological behavior of formulations. The findings enhance the conceptualization of CH and LM delivery, providing novel strategies for investigating prescription factors' bioactivity.
GPCRs identified on mitochondrial membranes: New therapeutic targets for diseases
Yanxin Pan, Ning Ji, Lu Jiang, Yu Zhou, Xiaodong Feng, Jing Li, Xin Zeng, Jiongke Wang, Ying-Qiang Shen, Qianming Chen
, Available online  , doi: 10.1016/j.jpha.2024.101178
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G protein-coupled receptors (GPCRs) are the largest family of membrane proteins in eukaryotes, with nearly 800 genes coding for these proteins. They are involved in many physiological processes, such as light perception, taste and smell, neurotransmitter, metabolism, endocrine and exocrine, cell growth and migration. Importantly, GPCRs and their ligands are the targets of approximately one third of all marketed drugs. GPCRs are traditionally known for their role in transmitting signals from the extracellular environment to the cell's interior via the plasma membrane. However, emerging evidence suggests that GPCRs are also localized on mitochondria, where they play critical roles in modulating mitochondrial functions. These mitochondrial GPCRs (mGPCRs) can influence processes such as mitochondrial respiration, apoptosis, and reactive oxygen species (ROS) production. By interacting with mitochondrial signaling pathways, mGPCRs contribute to the regulation of energy metabolism and cell survival. Their presence on mitochondria adds a new layer of complexity to the understanding of cellular signaling, highlighting the organelle's role as not just an energy powerhouse but also a crucial hub for signal transduction. This expanding understanding of mGPCR function on mitochondria opens new avenues for research, particularly in the context of diseases where mitochondrial dysfunction plays a key role. Abnormalities in the phase conductance pathway of GPCRs located on mitochondria are closely associated with the development of systemic diseases such as cardiovascular disease, diabetes, obesity and Alzheimer's disease. In this review, we examined the various types of GPCRs identified on mitochondrial membranes and analyzed the complex relationships between mGPCRs and the pathogenesis of various diseases. We aim to provide a clearer understanding of the emerging significance of mGPCRs in health and disease, and to underscore their potential as therapeutic targets in the treatment of these conditions.
Biological exposure and health risks of arsenic species from medicinal leeches at major exposure points in humans
Yaolei Li, Jing Fan, Hailiang Li, Xianlong Cheng, Hongyu Jin, Feng Wei, Shuangcheng Ma
, Available online  , doi: 10.1016/j.jpha.2024.101177
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In Silico Prediction of pKa Values Using Explainable Deep Learning Methods
Chen Yang, Changda Gong, Zhixing Zhang, Jiaojiao Fang, Weihua Li, Guixia Liu, Yun Tang
, Available online  , doi: 10.1016/j.jpha.2024.101174
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pKa significantly influences the ADMET properties of molecules and is a crucial indicator in drug research. Given the rapid and accurate characteristics of computational methods, their role in predicting drug properties is increasingly important. Although many pKa prediction models currently exist, they often focus on enhancing model precision while neglecting interpretability. In this study, we present GraFpKa, a pKa prediction model using graph neural networks (GNNs) and molecular fingerprints. The results show that our acidic and basic models achieved mean absolute errors (MAEs) of 0.621 and 0.402, respectively, on the test set, demonstrating good predictive performance. Notably, to improve interpretability, GraFpKa also incorporates Integrated Gradients (IGs), providing a clearer visual description of the atoms significantly affecting the pKa values. The high reliability and interpretability of GraFpKa ensure accurate pKa predictions while also facilitating a deeper understanding of the relationship between molecular structure and pKa values, making it a valuable tool in the field of pKa prediction.
Development and application of chiral separation technology based on chiral metalorganic frameworks
Gege Zhu, Li Ge, Xinyu Li, Bing Niu, Qin Chen, Dan Zhong, Xiaodong Sun
, Available online  , doi: 10.1016/j.jpha.2024.101176
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Chirality is not only a natural phenomenon but also a bridge between chemistry and life sciences. An effective way to obtain a single enantiomer is through racemates resolution. Recent literature shows that chiral metal-organic frameworks (CMOFs) have many applications in various fields because of their diverse topologies and functionalities. This review outlines the design idea and summarizes the latest synthesis strategies and applications of CMOFs. It highlights key advances and issues in the separation domain. In conclusion, the review provides perspectives on the challenges and prospective advancements of CMOFs materials and CMOFs-based separation technologies.
Characterization of preclinical radio ADME properties of ARV-471 for predicting human PK using PBPK modeling
Yifei He, Chenggu Zhu, Peng Lei, Chen Yang, Yifan Zhang, Yuandong Zheng, Xingxing Diao
, Available online  , doi: 10.1016/j.jpha.2024.101175
Abstract(102) HTML Full Text PDF(8)
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Proteolysis-targeting chimeras (PROTACs) represent a promising class of drugs that can target disease-causing proteins more effectively than traditional small molecule inhibitors can, potentially revolutionizing drug discovery and treatment strategies. The links between in vitro and in vivo data are poorly understood, hindering a comprehensive understanding of the absorption, distribution, metabolism, and excretion (ADME) of PROTACs. In this work, 14C-labeled vepdegestrant (ARV-471), which is currently in phase III clinical trials for breast cancer, was synthesized as a model PROTAC to characterize its preclinical ADME properties and simulate its clinical pharmacokinetics (PK) by establishing a physiologically based pharmacokinetics (PBPK) model. For in vitro-in vivo extrapolation (IVIVE), hepatocyte clearance correlated more closely with in vivo rat PK data than liver microsomal clearance did. PBPK models, which were initially developed and validated in rats, accurately simulate ARV-471's PK across fed and fasted states, with parameters within 1.75-fold of the observed values. Human models, informed by in vitro ADME data, closely mirrored postoral dose plasma profiles at 30 mg. Furthermore, no human-specific metabolites were identified in vitro and the metabolic profile of rats could overlap that of humans. This work presents a roadmap for developing future PROTAC medications by elucidating the correlation between in vitro and in vivo characteristics.
New insights into the dule roles CDK12 in human cancers: mechanisms and interventions for cancer therapy
Wei Dai, Dong Xie, Hao Huang, Jingxuan Li, Caiyao Guo, Fuqiang Cao, Luo Yang, Chengyong Zhong, Shenglan Liu
, Available online  , doi: 10.1016/j.jpha.2024.101173
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The dysregulation of cyclin-dependent kinase 12 (CDK12), which may result from genomic alterations or modulation by upstream effectors, is implicated in cancer oncogenesis and progression. CDK12 overexpression or activation is sufficient to induce tumor initiation, recurrence, and therapeutic resistance. However, CDK12 may also exert tumor-suppressive functions in a context-dependent manner. Therefore, caution is warranted when targeting CDK12 in future clinical trials. A comprehensive elucidation of the dual roles and underlying mechanisms of CDK12 in carcinogenesis is urgently needed to advance precision oncology. This review provides an overview of the current understanding of the dysregulation and biological roles of CDK12 in cancer. Subsequently, we systematically summarize the functions and mechanisms of the oncogenic and tumor-suppressive roles of CDK12 in different contexts. Finally, we discuss the potential of CDK12 as a novel therapeutic target and its implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.
Exosomes in ovarian cancer: impact on drug resistance and advances in SERS detection techniques
Biqing Chen, Xiaohong Qiu, Yang Li
, Available online  , doi: 10.1016/j.jpha.2024.101170
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Ovarian cancer is a prevalent gynecological malignancy with high mortality and low survival rates. The absence of specific symptoms in early stages often leads to late-stage diagnoses. Standard treatment typically includes surgery followed by platinum and paclitaxel chemotherapy. Exosomes, nanoscale vesicles released by various cell types, are key in intercellular communication, carrying biologically active molecules like proteins, lipids, enzymes, mRNA, and miRNAs. They are involved in tumor microenvironment remodeling, angiogenesis, metastasis, and chemoresistance in ovarian cancer. Emerging research highlights exosomes as drug carriers and therapeutic targets to suppress anti-tumor immune responses. Surface-Enhanced Raman Scattering (SERS) enables multiplexed, sensitive, and rapid detection of exosome surface proteins, offering advantages such as low background noise, no photobleaching, robustness, and high sensitivity over other detection methods. This review explores the relationship between exosomes and chemoresistance in ovarian cancer, examining the mechanisms by which exosomes contribute to drug resistance and their clinical implications. The goal is to provide new insights into chemoresistance mechanisms, improve diagnosis and intervention strategies, and enhance chemotherapy sensitivity in clinical treatments. In addition, the prospects of exosomes as drug carriers to resist chemical resistance and improve the survival of ovarian cancer patients are summarized. This article emphasizes the role of SERS in detecting ovarian cancer exosomes and advances in exosome detection.
Aldolase A accelerates hepatocarcinogenesis by refactoring c-Jun transcription
Xin Yang, Guang-Yuan Ma, Xiao-Qiang Li, Na Tang, Yang Sun, Xiao-Wei Hao, KeHan Wu, Yu-Bo Wang, Wen Tian, Xin Fan, Zezhi Li, Caixia Feng, Xu Chao, Yu-Fan Wang, Yao Liu, Di Li, Wei Cao
, Available online  , doi: 10.1016/j.jpha.2024.101169
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Hepatocellular carcinoma (HCC) expresses abundant glycolytic enzymes and displays comprehensive glucose metabolism reprogramming. Aldolase A (ALDOA) plays a prominent role in glycolysis; however, little is known about its role in HCC development. In the present study, we aim to explore how ALDOA is involved in HCC proliferation. HCC proliferation was markedly suppressed both in vitro and in vivo following ALDOA knockout, which is consistent with ALDOA overexpression encouraging HCC proliferation. Mechanistically, ALDOA knockout partially limits the glycolytic flux in HCC cells. Meanwhile, ALDOA translocated to nuclei and directly interacted with c- Jun to facilitate its Thr93 phosphorylation by P21-activated protein kinase; ALDOA knockout markedly diminished c-Jun Thr93 phosphorylation and then dampened c-Jun transcription function. A crucial site Y364 mutation in ALDOA disrupted its interaction with c-Jun, and Y364S ALDOA expression failed to rescue cell proliferation in ALDOA deletion cells. In HCC patients, the expression level of ALDOA was correlated with the phosphorylation level of c-Jun (Thr93) and poor prognosis. Remarkably, hepatic ALDOA was significantly upregulated in the promotion and progression stages of diethylnitrosamine-induced HCC models, and the knockdown of ALDOA strikingly decreased HCC development in vivo. Our study demonstrated that ALDOA is a vital driver for HCC development by activating c-Jun-mediated oncogene transcription, opening additional avenues for anti-cancer therapies.
Advances and challenges in drug design against dental caries: application of in silico approaches
Zhongxin Chen, Xinyao Zhao, Hanyu Zheng, Yufei Wang, Linglin Zhang
, Available online  , doi: 10.1016/j.jpha.2024.101161
Abstract(51) HTML Full Text PDF(5)
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Dental caries, a chronic disease characterized by tooth decay, occupies the second position in terms of disease burden and is primarily caused by cariogenic bacteria, especially Streptococcus mutans, because of its acidogenic, aciduric, and biofilm-forming capabilities. Developing novel targeted anti-virulence agents is always a focal point in caries control to overcome the limitations of conventional anti-virulence agents. The current study represents an up-to-date review of in silico approaches of drug design against dental caries, which have emerged more and more powerful complementary to biochemical attempts. Firstly, we categorize the in silico approaches into computer-aided drug design (CADD) and AI-assisted drug design (AIDD) and highlight the specific methods and models they contain respectively. Subsequently, we detail the design of anti-virulence drugs targeting single or multiple cariogenic virulence targets of S. mutans, such as glucosyltransferases (Gtfs), antigen I/II (AgI/II), sortase A (SrtA), the VicRK signal transduction system and superoxide dismutases (SODs). Finally, we outline the current opportunities and challenges encountered in this field to aid future endeavors and applications of CADD and AIDD in anti-virulence drug design.
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(249) HTML Full Text PDF(22)
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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(76) HTML Full Text PDF(1)
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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.
Inhibition of KLK8 Promotes Pulmonary Endothelial Repair by Restoring the VE-cadherin/Akt/FOXM1 Pathway
Ying Zhao, Hui Ji, Feng Han, Qing-Feng Xu, Hui Zhang, Di Liu, Juan Wei, Dan-Hong Xu, Lai Jiang, Jian-Kui Du, Ping-Bo Xu, Yu-Jian Liu, Xiao-Yan Zhu
, Available online  , doi: 10.1016/j.jpha.2024.101153
Abstract(94) HTML Full Text PDF(9)
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A review of research methods for elucidating the microstructure of pharmaceutical preparations
Peng Yan, Zhiyuan Hou, Jinsong Ding
, Available online  , doi: 10.1016/j.jpha.2024.101156
Abstract(48) HTML Full Text PDF(5)
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The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes, such as drug release, content uniformity, and stability, which greatly impact the safety and efficacy of drugs. Unlike the inherent molecular structures of active pharmaceutical ingredients and excipients, the microstructures of pharmaceutical preparations are developed during the formulation process, presenting unique analytical challenges. In this review, we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations, including X-ray imaging, scanning electron microscopy, atomic force microscopy, Raman spectroscopy, infrared spectroscopy, and rheometer technology. Subsequently, we highlight the applications, advantages, and limitations of these methods. Finally, we discuss the current challenges and future perspectives in this field. This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations, offering new insights and potential advancements in their development.
PU.1 regulation of type 1 dendritic cell function via NF-κB pathway in inhibition of non-small cell lung cancer progression
Tingting Wang, Yishuo Li, Qiongyu Duan, Chunlei Wang, Yixian Wang, Tianyu Hu
, Available online  , doi: 10.1016/j.jpha.2024.101154
Abstract(216) HTML Full Text PDF(2)
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This research investigates the regulatory role of the transcription factor PU.1 in type 1 conventional dendritic cells (cDC1) and its therapeutic potential of modulating the nuclear factor kappaB (NF-κB) cells signaling pathway in non-small cell lung cancer (NSCLC). Utilizing single-cell transcriptome sequencing and comprehensive bioinformatics tools, including the CIBERSORT algorithm, we analyzed the immune cell landscape within NSCLC tissues. Our analysis revealed distinct NSCLC subtypes and delineated the developmental trajectories and functional distinctions of cDC1 cells. Key differentially expressed genes (DEGs) and pivotal functional modules within these cells were identified, highlighting PU.1 as a critical mediator underexpressed in NSCLC samples. Functionally,PU.1 demonstrated the induction of the NF-κB pathway, which led to inhibited tumor proliferation and enhanced activation of cDC1, thereby suggesting its role in tumor immune surveillance. In vivo models confirmed the suppressive effect of PU.1 on NSCLC progression, mediated through its influence on cDC1 functionality via the NF-κB pathway. These findings propose PU.1 as a promising target for NSCLC therapeutic strategies, emphasizing the importance of transcriptional regulators in the tumor microenvironment.
Targeting tumor metabolism to augment CD8+ T cell anti-tumor immunity
Huan Liu, Wenyong Yang, Jingwen Jiang
, Available online  , doi: 10.1016/j.jpha.2024.101150
Abstract(92) HTML Full Text PDF(15)
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CD8+ T cell-based immune-therapeutics, including immune checkpoint inhibitors and adoptive cell therapies (TILs, TCR-T, CAR-T), have achieved significant successes and prolonged patient survival to varying extents and even achieved cure in some cases. However, immunotherapy resistance and tumor insusceptibility frequently occur, leading to treatment failure. Recent evidences have highlighted the ponderance of tumor cells metabolic reprogramming in establishing an immunosuppressive milieu through the secretion of harmful metabolites, immune-inhibitory cytokines, and alteration of gene expression, which suppress the activity of immune cells, particularly CD8+ T cells to evade immune surveillance. Therefore, targeting tumor cell metabolic adaptations to reshape the immune microenvironment holds promise as an immunomodulatory strategy to facilitate immunotherapy. Here, we summarize recent advances in the crosstalk between immunotherapy and tumor reprogramming, focusing on the regulatory mechanisms underlying tumor cell glucose metabolism, amino acid metabolism, and lipid metabolism in influencing CD8+ T cells to provide promising metabolic targets or combinational strategies for immunotherapy.
Hypothalamic lipidomics reveals that AMPK-FA metabolism mediates the energy-balancing effect of the four typical ‘hot’ herbs on hypothyroidism
Yangyang Wang, Yizhou Rong, Liangce Chen, Qi Cui, Haixue Kuang, Bo Yang
, Available online  , doi: 10.1016/j.jpha.2024.101151
Abstract(82) HTML Full Text PDF(5)
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Natural products for the treatment of age-related macular degeneration: new insights focusing on mitochondrial quality control and cGAS/STING pathway
Xuelu Xie, Shan Lian, Wenyong Yang, Sheng He, Jingqiu He, Yuke Wang, Yan Zeng, Fang Lu, Jingwen Jiang
, Available online  , doi: 10.1016/j.jpha.2024.101145
Abstract(31) HTML Full Text PDF(4)
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Age-related macular degeneration (AMD) is a disease that affects the vision of elderly individuals worldwide. Although current therapeutics have shown effectiveness against AMD, some patients may remain unresponsive and continue to experience disease progression. Therefore, in-depth knowledge of the mechanism underlying AMD pathogenesis is urgently required to identify potential drug targets for AMD treatment. Recently, studies have suggested that dysfunction of mitochondria can lead to the aggregation of reactive oxygen species (ROS) and activation of the cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) innate immunity pathways, ultimately resulting in sterile inflammation and cell death in various cells, such as cardiomyocytes and macrophages. Therefore, combining strategies targeting mitochondrial dysfunction and inflammatory mediators may hold great potential in facilitating AMD management. Notably, emerging evidence indicates that natural products targeting mitochondrial quality control (MQC) and the cGAS/STING innate immunity pathways exhibit promise in treating AMD. Here, we summarize phytochemicals that could directly or indirectly influence the MQC and the cGAS/STING innate immunity pathways, as well as their interconnected mediators, which have the potential to mitigate oxidative stress and suppress excessive inflammatory responses, thereby hoping to offer new insights into therapeutic interventions for AMD treatment.
Polyphyllin VII promotes hepatic stellate cell ferroptosis via the HIC1/CX3CL1/GPX4 axis
Feng Jiang, Xinmiao Li, Mengyuan Li, Weizhi Zhang, Yifei Li, Lifan Lin, Lufan He, Jianjian Zheng
, Available online  , doi: 10.1016/j.jpha.2024.101147
Abstract(78) HTML Full Text PDF(4)
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Ferroptosis has been shown to mediate the development of fibrosis. Polyphyllin VII (PP7), a bioactive component of Paris polyphylla, exhibits potent anti-inflammatory activity and can significantly alleviate liver fibrosis. In this study, treatment with PP7 significantly inhibited the proliferation and activation of hepatic stellate cells (HSCs), which could be suppressed by a ferroptosis inhibitor. In addition, it promoted HSC ferroptosis by suppressing glutathione peroxidase 4 (GPX4) and enhanced the expression of CX3C chemokine ligand 1 (CX3CL1). Depletion of CX3CL1 attenuated the effects of PP7 on the activation and ferroptosis of HSCs and the expression of GPX4. Notably, CX3CL1 directly interacted with GPX4, triggering HSC ferroptosis. The transcription factor hypermethylated in cancer 1 (HIC1), which binds to the CX3CL1 promoter, increased the expression of CX3CL1. Its absence resulted in downregulation of CX3CL1, suppressing the GPX4-dependent ferroptosis of PP7-treated HSCs and promoting their activation. HIC1 was found to directly interact with PP7 at the GLY164 site. Co-culture experiments showed that PP7-induced HSC ferroptosis attenuated macrophage recruitment by regulating inflammation-related genes. HSC-specific inhibition of HIC1 counteracted PP7-induced collagen depletion and HSC ferroptosis in vivo. These findings suggest that PP7 induces HSC ferroptosis through the HIC1/CX3CL1/GPX4 axis.
Mitochondrial quality control disorder in neurodegenerative disorders: potential and advantages of traditional Chinese medicines
Lei Xu, Tao Zhang, Baojie Zhu, Honglin Tao, Yue Liu, Xianfeng Liu, Yi Zhang, Xianli Meng
, Available online  , doi: 10.1016/j.jpha.2024.101146
Abstract(62) HTML Full Text PDF(1)
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Mitochondrial quality control disorder in neurodegenerative disorders: Potential and advantages of traditional Chinese medicines Abstract Neurodegenerative disorders (NDDs) are prevalent chronic conditions characterized by progressive synaptic loss and pathological protein alterations. Increasing evidence suggested that mitochondrial quality control (MQC) serves as the key cellular process responsible for clearing misfolded proteins and impaired mitochondria. Herein, we provided a comprehensive analysis of the mechanisms through which MQC mediates the onset and progression of NDDs, emphasizing mitochondrial dynamic stability, the clearance of damaged mitochondria, and the generation of new mitochondria. In addition, traditional Chinese medicines (TCMs) and their active monomers targeting MQC in NDD treatment have been demonstrated. Consequently, we compiled the TCMs that show great potential in the treatment of NDDs by targeting MQC, aiming to offer novel insights and a scientific foundation for the use of MQC stabilizers in NDD prevention and treatment.
Probing the Biological Efficacy and Mechanistic Pathways of Natural Compounds in Breast Cancer Therapy via the Hedgehog Signaling Route
Yining Cheng, Wenfeng Zhang, Qi Sun, Xue Wang, Qihang Shang, Jingyang Liu, Yubao Zhang, Ruijuan Liu, Changgang Sun
, Available online  , doi: 10.1016/j.jpha.2024.101143
Abstract(54) HTML Full Text PDF(2)
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Breast cancer (BC) is one of the most prevalent malignant tumors affecting women worldwide, with its incidence rate continuously increasing. As a result, treatment strategies for this disease have received considerable attention. Research has highlighted the crucial role of the Hedgehog (Hh) signaling pathway in the initiation and progression of BC, particularly in promoting tumor growth and metastasis. Therefore, molecular targets within this pathway represent promising opportunities for the development of novel BC therapies. This study aims to elucidate the therapeutic mechanisms by which natural compounds modulate the Hh signaling pathway in BC. By conducting a comprehensive review of various natural compounds—including polyphenols, terpenes, and alkaloids—we reveal both common and unique regulatory mechanisms that influence this pathway. This investigation represents the first comprehensive analysis of five distinct mechanisms through which natural compounds modulate key molecules within the Hh pathway and their impact on the aggressive behaviors of BC. Furthermore, by exploring the structure-activity relationships between these compounds and their molecular targets, we shed light on the specific structural features that enable natural compounds to interact with various components of the Hh pathway. These novel insights contribute to advancing the development and clinical application of natural compound-based therapeutics. Our thorough review not only lays the groundwork for exploring innovative BC treatments but also opens new avenues for leveraging natural compounds in cancer therapy.
Inhibiting Neddylation: A New Strategy for Tumor Therapy
Jian Sun, Cui Liu, Changhui Lang, Jing Wang, Qingxiang Li, Chang Peng, Zuochen Du, Yan Chen, Pei Huang
, Available online  , doi: 10.1016/j.jpha.2024.101140
Abstract(86) HTML Full Text PDF(5)
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Neddylation is a crucial posttranslational modification that involves the attachment of neural precursor cellexpressed developmentally downregulated protein 8 (NEDD8) to a lysine residue in the substrate via the sequential actions of the E1 NEDD8-activating enzyme (NAE), E2 NEDD8-conjugating enzyme (E2), and E3 NEDD8-ligase (E3). The most extensively studied substrates of neddylation are members of the cullin family, which act as scaffold components for cullin ring E3 ubiquitin ligases (CRLs). Since cullin neddylation activates CRLs, which are frequently overactive in tumors, inhibiting neddylation has emerged as a promising strategy for developing novel antitumor therapies. This review explores the antitumor effects of inhibiting neddylation that leads to the inactivation of CRLs and provides a summary of known inhibitors that target protein-protein interactions (PPIs) within the neddylation enzymatic cascade.
Huangqin decoction inhibits colorectal inflammatory cancer transformation by improving gut microbiome-mediated metabolic dysfunction
Lu Lu, Yuan Li, Hang Su, Sisi Ren, Yujing Liu, Gaoxuan Shao, Weiwei Liu, Guang Ji, Hanchen Xu
, Available online  , doi: 10.1016/j.jpha.2024.101138
Abstract(109) HTML Full Text PDF(3)
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Colorectal inflammatory cancer transformation poses a major risk to patients with colitis. Patients with chronic intestinal inflammation have an approximately 2- 3fold increased risk of developing colorectal cancer (CRC). Unfortunately, there is currently no effective intervention available. Huangqin decoction (HQD), a wellknown traditional Chinese medicine (TCM) formula, is frequently clinically prescribed for treating patients with colitis, and its active ingredients have effective antitumour efficacy. Nonetheless, the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear. A strategy integrating metagenomic, lipidomic, and messenger RNA (mRNA) sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome, metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation. Our study revealed that HQD suppressed colorectal inflammatory cancer transformation, which was associated with enhanced intestinal barrier function, decreased the inflammatory response, and regulation of the gut microbiome. Notably, cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis. Moreover, gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism, especially the remodeling of arachidonic acid metabolism, which was associated with the amelioration of pathological transformation. Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase (ALOX12) were affected by HQD treatment, and no obvious protective effect of HQD was observed in ALOX12-/- mice, which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation. In summary, multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory colorectal cancer.
Diffusion-based generative drug-like molecular editing with chemical natural language
Jianmin Wang, Peng Zhou, Zixu Wang, Wei Long, Yangyang Chen, Kyoung Tai No, Dongsheng Ouyang, Jiashun Mao, Xiangxiang Zeng
, Available online  , doi: 10.1016/j.jpha.2024.101137
Abstract(121) HTML Full Text PDF(10)
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Recently, diffusion models have emerged as a promising paradigm for molecular design and optimization. However, most diffusion-based molecular generative models focus on modeling 2D graphs or 3D geometries, with limited research on molecular sequence diffusion models. The International Union of Pure and Applied Chemistry (IUPAC) names are more akin to chemical natural language than the Simplified Molecular Input Line Entry System (SMILES) for organic compounds. In this work, we apply an IUPAC-guided conditional diffusion model to facilitate molecular editing from chemical natural language to chemical language (SMILES) and explore whether the pre-trained generative performance of diffusion models can be transferred to chemical natural language. We propose DiffIUPAC, a controllable molecular editing diffusion model that converts IUPAC names to SMILES strings. Evaluation results demonstrate that our model outperforms existing methods and successfully captures the semantic rules of both chemical languages. Chemical space and scaffold analysis show that the model can generate similar compounds with diverse scaffolds within the specified constraints. Additionally, to illustrate the model's applicability in drug design, we conducted case studies in functional group editing, analogue design and linker design.
Raman Analysis of Lipids in Cells: Current Applications and Future Prospects
Yixuan Zhou, Yuelin Xu, Xiaoli Hou, Daozong Xia
, Available online  , doi: 10.1016/j.jpha.2024.101136
Abstract(96) HTML Full Text PDF(5)
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Lipids play an important role in the regulation of cell life processes. Although there are various lipid detection methods, Raman spectroscopy, a non-invasive technique, provides the detailed chemical composition of lipid profiles without a complex sample preparation procedure and possesses greater potential in basic biology, clinical diagnosis and disease therapy. In this review, we summarized the characteristics and advantages of Raman-based techniques and their primary contribution to illustrating cellular lipid metabolism.
Open flow microperfusion to assess local drug concentrations in the buccal mucosa
Laura Wiltschko, Paula Fischer, Simon Schwingenschuh, Reingard Raml, Georg Raber, Thomas Birngruber, Eva Roblegg
, Available online  , doi: 10.1016/j.jpha.2024.101135
Abstract(50) HTML Full Text PDF(0)
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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(72) HTML Full Text PDF(2)
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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.
The biological roles of exosome-encapsulated traditional Chinese medicine monomers in neuronal disorders
Chen Pang, Jie Zhang, Yujin Gu, Qili Zhang, Yanfang Zhao
, Available online  , doi: 10.1016/j.jpha.2024.101131
Abstract(55) HTML Full Text PDF(1)
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A traditional Chinese medicine (TCM) monomer is a bioactive compound extracted from Chinese herbal medicines possessing determined biological activity and pharmacological effects, that has gained much attention for treating neuronal diseases. However, the application of TCM monomers is limited by their low solubility and poor ability to cross the blood-brain barrier (BBB). Exosomes are small extracellular vesicles ranging in size from 30– 150 nm in diameter and can be used as drug delivery carriers that directly target cells or tissues with unique advantages, including low toxicity, low immunogenicity, high stability in blood, and the ability to cross the BBB. This review discusses the biogenesis, components, stability, surface modification, isolation technology, advantages, and disadvantages of exosomes as drug carriers and compares exosomes and other similar drug delivery systems. Furthermore, exosome-encapsulated TCM monomers exert neuroprotective roles, such as anti-inflammation, anti-apoptosis, anti-mitophagy, and anti-oxidation, in various neuronal diseases, including Alzheimer's disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), and cerebral ischemia and reperfusion injury (CI/R), as well as anti-drug resistance, anti-tumorigenesis, anti-angiogenesis, and promotion of apoptosis in brain tumors, providing more inspiration to promote the development of an exosome-based delivery tool in targeted therapy for neuronal diseases.
Lycium Barbarum's Diabetes Secrets: A Comprehensive Review of Cellular, Molecular, and Epigenetic Targets with Immune Modulation and Microbiome Influence
Zeshan Ali, Aqsa Ayub, Ya wen Lin, Sonam Anis, Ishrat Khan, Shoaib Younas, Rana Adnan Tahir, Shulin Wang, Jianrong Li
, Available online  , doi: 10.1016/j.jpha.2024.101130
Abstract(57) HTML Full Text PDF(2)
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Diabetes, a metabolic disease stemming from impaired or defective insulin secretion, ranks among the most severe chronic illnesses globally. While several approved drugs exist for its treatment, they often come with multiple side effects. Therefore, there is a pressing need for safe and effective anti-diabetic medications. Traditional Chinese medicine has recognized Lycium barbarum (LB, goji berry) plant, commonly known as "wolfberry fruit" in China, for over 2,000 years. Natural compounds derived from LB show promise in reducing diabetes levels. Although research on the impact of LB on diabetes is still limited, our review aims to explore the potential of LB in reducing the risk of diabetes and examine the underlying mechanisms involved. LB can modulate diabetes through various pathways, such as inhibiting α-amylase and α-glucosidase activities, promoting β-cell proliferation, stimulating insulin secretion, inhibiting glucagon secretion, improving insulin resistance and glucose tolerance, and enhancing antioxidant and anti-inflammatory activities. Additionally, LB improves gut flora and immunomodulation, further aiding diabetes management. These findings highlight the potential clinical utility of LB in managing diabetes and its complications within the framework of evidence-based modern medicine.
Research and application of thermosensitive Pickering emulsion with X-ray and ultrasound dual-modal imaging functions for intra-arterial embolization treatment
Ling Li, Anran Guo, Haixia Sun, Yanbing Zhao, Qing Yao, Ling Zhang, Peng Shi, Hongan Tian, Min Zheng
, Available online  , doi: 10.1016/j.jpha.2024.101133
Abstract(41) HTML Full Text PDF(2)
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Transcatheter arterial embolization (TAE) is the mainstay for treating advanced hepatocellular carcinoma (HCC), and the performance of the embolization material is crucial in TAE. With the development of medical imaging and the birth of “X-ray-free” technologies, we designed a new dual-mode imaging material of dimethoxy tetraphenyl ethylene (DMTPE) via emulsification by mixing poly (N-isopropylacrylamide-co-acrylic acid) (PNA) with lipiodol and fluorocarbons, which was evaluated for temperature sensitivity, stability, and dual-mode visualization in vitro. Additionally, blood vessel casting embolization and renal artery imaging were assessed in healthy rabbits. In a rabbit model with a VX2 tumor, the effectiveness of transarterial embolization (TAE) for treating HCC was examined, with an emphasis on evaluating long-term outcomes of embolization and its effects on tumor growth, necrosis, and proliferation through imaging techniques. In vitro experiments confirmed that the temperature-sensitive dual-oil-phase Pickering emulsion had good flow, stable contrast, and embolism when the oil-to-oil ratio and water-to-oil ratio were both 7:3 (V/V) and stabilized with 8% PNA. Similarly, in vivo, arterial embolization confirmed the excellent properties of DMTPE prepared at the abovementioned ratios. It was observed that DMTPE not only has an antitumor effect but can also achieve dual imaging using X-rays and ultrasound, making it a promising excellent vascular embolization material for TAE in tumor treatment.
A disentangled generative model for improved drug response prediction in patients via sample synthesis
Kunshi Li, Bihan Shen, Fangyoumin Feng, Xueliang Li, Yue Wang, Na Feng, Zhixuan Tang, Liangxiao Ma, Hong Li
, Available online  , doi: 10.1016/j.jpha.2024.101128
Abstract(65) HTML Full Text PDF(5)
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Thalidomide mitigates Crohn's disease colitis by modulating gut microbiota, metabolites, and regulatory T cell immunity
Chao-Tao Tang, Yonghui Wu, Qing Tao, Chun-Yan Zeng, You-Xiang Chen
, Available online  , doi: 10.1016/j.jpha.2024.101121
Abstract(45) HTML Full Text PDF(2)
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Thalidomide (THA) is renowned for its potent anti-inflammatory properties. This study aimed to elucidate its underlying mechanisms in the context of Crohn’s disease (CD) development. Mouse colitis models were established by dextran sulfate sodium (DSS) treatment. Fecal microbiota and metabolites were analyzed by metagenomic sequencing and mass spectrometry, respectively. Antibiotic- treated mice served as models for microbiota depletion and transplantation. The expression of Forkhead box P3+ (FOXP3+) Regulatory T cells (Tregs) was measured by flow cytometry and immunohistochemical assay in colitis model and patient cohort. THA inhibited colitis in DSS–treated mice by altering the gut microbiota profile, with an increased abundance of probiotics Bacteroides fragilis (Bf), while pathogenic bacteria were depleted. In addition, THA increased beneficial metabolites bile acids and significantly restored gut barrier function. Transcriptomic profiling revealed that THA inhibited interleukin-17 (IL17), IL1β and cell cycle signaling. Fecal microbiota transplantation from THA-treated mice to microbiota-depleted mice partly recapitulated the effects of THA. Specifically, increased level of gut commensal Bf was observed, correlated with elevated levels of the microbial metabolite 7-Ketolithocholic acid (7-KA) following THA treatment. This microbial metabolite may stable FOXP3 expression by targeting the bile acid receptor farnesol X receptor 1(FXR1) to inhibit autophagy. An interaction between FOXP3 and FXR1 was identified, with binding regions localized to the FOXP3 domain (aa 238-335) and the FXR1 domain (aa 82-222), respectively. Conclusively, THA modulates the gut microbiota and metabolite profiles towards a more beneficial composition, enhances gut barrier function, promotes the differentiation of FOXP3+ Tregs and curbs pro-inflammatory pathways.
Altered serum metabolic profile in patients with autoimmune gastritis compared to other chronic gastritis
Jihua Shi, Yang Zhang, Yiran Wang, Yuxi Huang, Zhe Chen, Xue Xu, Wenbin Li, Dan Chen, Hao Luo, Qingfeng Luo, Ruiyue Yang, Xue Qiao
, Available online  , doi: 10.1016/j.jpha.2024.101104
Abstract(79) HTML Full Text PDF(4)
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Targeting ceramide-induced microglial pyroptosis: Icariin is a promising therapeutic therapy for Alzheimer's disease
Hongli Li, Qiao Xiao, Lemei Zhu, Jin Kang, Qiong Zhan, Weijun Peng
, Available online  , doi: 10.1016/j.jpha.2024.101106
Abstract(156) HTML Full Text PDF(24)
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Alzheimer’s disease (AD), a progressive dementia, is one of the most common neurodegenerative diseases. Clinical trial results of amyloid-β (Aβ) and tau regulators based on the pretext of straightforward amyloid and tau immunotherapy were disappointing. There are currently no effective strategies for slowing the progression of AD. Herein, we spotlight the dysregulation of lipid metabolism, particularly the elevation of ceramides (Cers), as a critical yet underexplored facet of AD pathogenesis. Our study delineates the role of Cers in promoting microglial pyroptosis, a form of programmed cell death distinct from apoptosis and necroptosis, characterized by cellular swelling, and membrane rupture mediated by the NLRP3 inflammasome pathway. Utilizing both in vivo experiments with APP/PS1 transgenic mice and in vitro assays with BV-2 microglial cells, we investigate the activation of microglial pyroptosis by Cers and its inhibition by Icariin (ICA), a flavonoid with known antioxidant and anti-inflammatory properties. Our findings reveal a significant increase in Cers levels and pyroptosis markers (NLRP3, apoptosis-associated speck-like protein containing a caspase recruitment domain, caspase-1, gasdermin D, and interleukin-18) in the brains of AD model mice, indicating a direct involvement of Cers in AD pathology through the induction of microglial pyroptosis. Conversely, ICA treatment effectively reduces these pyroptotic markers and Cer levels, thereby attenuating microglial pyroptosis and suggesting a novel therapeutic mechanism of action against AD. This study not only advances our understanding of the pathogenic role of Cers in AD but also introduces ICA as a promising candidate for AD therapy, capable of mitigating neuroinflammation and pyroptosis through the COX2-NLRP3 inflammasome-GSDMD axis. Our results pave the way for further exploration of Cer metabolism disorders in neurodegenerative diseases and highlight the therapeutic potential of targeting microglial pyroptosis in AD.
A promising strategy of brain targeted delivery for the treatment of Parkinson’s disease: Cyclodextrin supramolecular inclusion complex based thermosensitive gel
Yan-Qiu Wang, Li-Ming Wang, Li-Feng Han, Yi-Bing Chen, Yuan-Lu Cui
, Available online  , doi: 10.1016/j.jpha.2024.101102
Abstract(120) HTML Full Text PDF(2)
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Synergistic approach to combating triple-negative breast cancer: ddr1-targeted antibody-drug conjugate combined with pembrolizumab
Shoubing Zhou, Wenyu Li, Dan Zhao, Qiujun Zhang, Hu Liu, Tengchuan Jin, Yueyin Pan
, Available online  , doi: 10.1016/j.jpha.2024.101100
Abstract(97) HTML Full Text PDF(2)
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Discoidin domain receptor 1 (DDR1) is overexpressed in various tumors, such as triple-negative breast cancer (TNBC), and is rarely expressed in normal tissues. These characteristics make DDR1 a preferable target candidate for the construction of an antibody‒drug conjugate (ADC) for targeted therapy. Here, we investigated the preparation and preclinical efficacy of DDR1-DX8951, an ADC that includes an antiDDR1 monoclonal antibody conjugated to DX8951 by a cleavable GGFG linker. The anti-DDR1 monoclonal antibody was coupled to DX8951, producing the targeted therapy ADC, DDR1-DX8951. The antitumor activities of DDR1-DX8951 monotherapy or DDR1-DX8951 plus pembrolizumab were assessed in TNBC mouse models. DDR1-DX8951 can specifically target DDR1, be quickly internalized by TNBC cells, and reduce the viability of TNBC cells in vitro. The potent antitumor activity of DDR1-DX8951 was revealed in TNBC xenograft models. Importantly, our investigation demonstrated that DDR1-DX8951 plus pembrolizumab not only revealed the inhibitory efficacy on tumor growth and metastasis but also played an important role in improving the immunosuppressive tumor microenvironment of TNBC. Taken together, this investigation provides justification for large-sample studies to further assess the safety and efficacy of DDR1-DX8951 plus pembrolizumab for TNBC clinical trials.
Luteolin and its antidepressant properties: From mechanism of action to potential therapeutic application
Jiayu Zhou, Ziyi Wu, Ping Zhao
, Available online  , doi: 10.1016/j.jpha.2024.101097
Abstract(78) HTML Full Text PDF(0)
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Luteolin is a natural flavonoid compound exists in various fruits and vegetables. Recent studies have indicated that luteolin has variety pharmacological effects, including a wide range of antidepressant properties. Here, we systematically review the preclinical studies and limited clinical evidence on the antidepressant and neuroprotective effects of luteolin to fully explore its antidepressant power. Network pharmacology and molecular docking analyses contribute to a better understanding of the preclinical models of depression and antidepressant properties of luteolin. Seventeen preclinical studies were included that combined network pharmacology and molecular docking analyses to clarify the antidepressant mechanism of luteolin and its antidepressant targets. The antidepressant effects of luteolin may involve promoting intracellular noradrenaline (NE) uptake; inhibiting 5-hydroxytryptamine (5-HT) reuptake; upregulating the expression of synaptophysin, postsynaptic density protein 95, brain- derived neurotrophic factor, B cell lymphoma protein-2, superoxide dismutase, and glutathione S-transferase; and decreasing the expression of malondialdehyde, caspase- 3, and amyloid-beta peptides. The antidepressant effects of luteolin are mediated by various mechanisms, including anti-oxidative stress, anti-apoptosis, anti-inflammation, anti-endoplasmic reticulum stress, dopamine transport, synaptic protection, hypothalamic-pituitary-adrenal axis regulation, and 5-HT metabolism. Additionally, we identified insulin-like growth factor 1 receptor (IGF1R), AKT serine/threonine kinase 1 (AKT1), prostaglandin-endoperoxide synthase 2 (PTGS2), estrogen receptor alpha (ESR1), and epidermal growth factor receptor (EGFR) as potential targets, luteolin has an ideal affinity for these targets, suggesting that it may play a positive role in depression through multiple targets, mechanisms, and pathways. However, the clinical efficacy of luteolin and its potential direct targets must be confirmed in further multicenter clinical case-control and molecular targeting studies.
A review of transformers in drug discovery and beyond
Jian Jiang, Long Chen, Lu Ke, Bozheng Dou, Chunhuan Zhang, Hongsong Feng, Yueying Zhu, Huahai Qiu, Bengong Zhang, Guowei Wei
, Available online  , doi: 10.1016/j.jpha.2024.101081
Abstract(138) HTML Full Text PDF(15)
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Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics, drug target identification, transformer-enabled drug virtual screening, drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.
Screen of FDA-approved drug library identifies Vitamin K as anti-ferroptotic drug for osteoarthritis therapy through Gas6
Yifeng Shi, Sunlong Li, Shuhao Zhang, Caiyu Yu, Jiansen Miao, Shu Yang, Yan Chen, Yuxuan Zhu, Xiaoxiao Huang, Chencheng Zhou, Hongwei Ouyang, Xiaolei Zhang, Xiangyang Wang
, Available online  , doi: 10.1016/j.jpha.2024.101092
Abstract(113) HTML Full Text PDF(11)
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Ferroptosis of chondrocytes is a significant contributor to osteoarthritis (OA), for which there is still a lack of safe and effective therapeutic drugs targeting ferroptosis. Here, we screen for anti-ferroptotic drugs in Food and Drug Administration (FDA)-approved drug library via a high-throughput manner in chondrocytes. We identified a group of FDA-approved anti- ferroptotic drugs, among which vitamin K showed the most powerful protective effect. Further study demonstrated that vitamin K effectively inhibited ferroptosis and alleviated the extracellular matrix (ECM) degradation in chondrocytes. Intra-articular injection of vitamin K inhibited ferroptosis and alleviated OA phenotype in destabilization of the medial meniscus (DMM) mouse model. Mechanistically, transcriptome sequencing and knockdown experiments revealed that the anti-ferroptotic effects of vitamin K depended on growth arrest–specific 6 (Gas6). Furthermore, exogenous expression of Gas6 was found to inhibit ferroptosis through the AXL/PI3K/AKT axis. Together, we demonstrate that vitamin K inhibits ferroptosis and alleviates OA progression via enhancing Gas6 expression and its downstream pathway of AXL/PI3K/AKT axis, indicating vitamin K as well as Gas6 to serve as a potential therapeutic target for OA and other ferroptosis-related diseases.
Liquiritin improves macrophage degradation of engulfed tumor cells by promoting the formation of phagolysosomes via NOX2/gp91phox
Caiyi Yang, Kehan Chen, Yunliang Chen, Xuting Xie, Pengcheng Li, Meng Zhao, Junjie Liang, Xueqian Xie, Xiaoyun Chen, Yanping Cai, Bo Xu, Qing Wang, Lian Zhou, Xia Luo
, Available online  , doi: 10.1016/j.jpha.2024.101093
Abstract(53) HTML Full Text PDF(2)
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The incomplete degradation of tumour cells by macrophages (Mφ) is a contributing factor to tumour progression and metastasis, and the degradation function of Mφ is mediated through phagosomes and lysosomes. In our preliminary experiments, we found that overactivation of NADPH oxidase 2 (NOX2) reduced the ability of Mφ to degrade engulfed tumour cells. Above this, we screened out liquiritin from Glycyrrhiza uralensis Fisch, which can significantly inhibit NOX2 activity and inhibit tumours, to elucidate that suppressing NOX2 can enhance the ability of Mφ to degrade tumour cells. We found that the tumour environment could activate the NOX2 activity in Mφ phagosomes, causing Mφ to produce excessive reactive oxygen species (ROS), thus prohibiting the formation of phagolysosomes before degradation. Conversely, inhibiting NOX2 in Mφ by liquiritin can reduce ROS and promote phagosome-lysosome fusion, therefore improving the enzymatic degradation of tumour cells after phagocytosis, and subsequently promote T cell activity by presenting antigens. We further confirmed that liquiritin down-regulated the expression of the NOX2 specific membrane component protein gp91 phox, blocking its binding to the NOX2 cytoplasmic component proteins p67 phox and p47 phox, thereby inhibiting the activity of NOX2. This study elucidates the specific mechanism by which Mφ cannot degrade tumour cells after phagocytosis, and indicates that liquiritin can promote the ability of Mφ to degrade tumour cells by suppressing NOX2.
Identifying purgative targets of Sennoside A via in situ biotransformation of prodrugbased probes
Zhen Liu, Xinyue Geng, Xinyue Liu, Mengru Li, Xiang Li, Zhixin Zhang, Gan Luo, Ying Wang, Xiaoyan Gao
, Available online  , doi: 10.1016/j.jpha.2024.101078
Abstract(99) HTML Full Text PDF(13)
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Exploring the Impact of the Liver-Intestine-Brain Axis on Brain Function in Non-Alcoholic Fatty Liver Disease
Jingting Zhang, Keyan Chen, Fu Chen
, Available online  , doi: 10.1016/j.jpha.2024.101077
Abstract(286) HTML Full Text PDF(15)
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This study investigates the molecular complexities of Non-alcoholic Fatty Liver Disease (NAFLD)-induced brain dysfunction, with a focus on the liver-intestine-brain axis and potential therapeutic interventions. The main objectives include understanding critical microbiota shifts in NAFLD, exploring altered metabolites, and identifying key regulatory molecules influencing brain function. The methods employed encompassed 16S rRNA sequencing to scrutinize stool microbiota in NAFLD patients and healthy individuals, non-targeted metabolomics using LC-MS to uncover elevated levels of deoxycholic acid (DCA) in NAFLD mice, and single-cell RNA sequencing to pinpoint the pivotal gene Hpgd in microglial cells and its downstream janus kinase 2/signal transducer and activator of transcription 3 (Jak2/Stat3) signaling pathway. Behavioral changes and brain function were assessed in NAFLD mice with and without Fecal Microbiota Transplantation (FMT) treatment, utilizing various assays and analyses. The results revealed significant differences in microbiota composition, with increased levels of Bacteroides in NAFLD patients. Additionally, elevated DCA levels were observed in NAFLD mice, and FMT treatment demonstrated efficacy in ameliorating liver function and brain dysfunction. Hpgd inhibition by DCA activated the Jak2/Stat3 pathway in microglial cells, leading to inflammatory activation, inhibition of mitochondrial autophagy, induction of neuronal apoptosis, and reduction in neuronal action potentials. This study elucidates the intricate molecular mechanisms underlying the liver-gut-brain axis in NAFLD, and the identification of increased DCA and the impact of Jak2/Stat3 signaling on microglial cells highlight potential therapeutic targets for addressing NAFLD-induced brain dysfunction.
An improved reporter gene assay for evaluating the biological activity of recombinant human growth hormone
Xiaoming Zhang, Heyang Li, Ying Huang, Ping Lv, Lvyin Wang, Kezheng Xu, Yi Li, Xinyue Hu, Yue Sun, Cheng-gang Liang, Jing Li
, Available online  , doi: 10.1016/j.jpha.2024.101073
Abstract(89) HTML Full Text PDF(2)
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Pharmacological modulation of mitochondrial function as novel strategies for treating intestinal inflammatory diseases and colorectal cancer
Boya Wang, Xinrui Guo, Lanhui Qin, Liheng He, Jingnan Li, Xudong Jin, Dapeng Chen, Guangbo Ge
, Available online  , doi: 10.1016/j.jpha.2024.101074
Abstract(194) HTML Full Text PDF(9)
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Inflammatory bowel disease (IBD) is a chronic and recurrent intestinal disease, and has become a major global health issue. Individuals with IBD face an elevated risk of developing colorectal cancer (CRC), and recent studies have indicated that mitochondrial dysfunction plays a pivotal role in the pathogenesis of both IBD and CRC. This review covers the pathogenesis of IBD and CRC, focusing on mitochondrial dysfunction, and explores pharmacological targets and strategies for addressing both conditions by modulating mitochondrial function. Additionally, recent advancements in the pharmacological modulation of mitochondrial dysfunction for treating IBD and CRC, encompassing mitochondrial damage, release of mitochondrial DNA (mtDNA) and impairment of mitophagy are thoroughly summarized. The review also provides a comprehensive overview of various natural compounds (such as flavonoids, alkaloids, and diterpenoids), Chinese medicines, and intestinal microbiota which can alleviate IBD and retarding the progression of CRC by modulating mitochondrial function. In the future, it will be imperative to develop more practical methodologies for real-time monitoring and accurate detection of mitochondrial function, which will greatly aid scientists in identifying more effective agents for treating IBD and CRC through modulation of mitochondrial function.
A tailored database combining reference compound-derived metabolite, metabolism platform and chemical characteristic of Chinese herb followed by activity screening: Application to Magnoliae Officinalis Cortex
Zhenzhen Xue, Yudong Shang, Lan Yang, Tao Li, Bin Yang
, Available online  , doi: 10.1016/j.jpha.2024.101066
Abstract(109) HTML Full Text PDF(6)
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A strategy combining a tailored database and high-throughput activity screening that discover bioactive metabolites derived from Magnoliae Officinalis Cortex (MOC) was developed and implemented to rapidly profile and discover bioactive metabolites in vivo derived from traditional Chinese medicine (TCM). The strategy possessed four characteristics: 1) The tailored database consisted of metabolites derived from big data-originated reference compound, metabolites predicted in silico, and MOC chemical profile-based pseudomolecular ions. 2) When profiling MOC-derived metabolites in vivo, attentions were paid not only on prototypes of MOC compounds and metabolites directly derived from MOC compounds, as reported by most papers, but also on isomerized metabolites and the degradation products of MOC compounds as well as their derived metabolites. 3) Metabolite traceability was performed, especially to distinguish isomeric prototypes-derived metabolites, and prototypes of MOC compounds as well as phase I metabolites derived from other MOC compounds. 4) Molecular docking was utilized for high-throughput activity screening and molecular dynamic simulation as well as zebrafish model were used for verification. Using this strategy, 134 metabolites were swiftly characterized after the oral administration of MOC to rats, and several metabolites were reported for the first time. Furthermore, 17 potential active metabolites were discovered by targeting the motilin, dopamine D2, and the serotonin type 4 (5-HT4) receptors, and their bioactivities were verified using molecular dynamic simulation and a zebrafish constipation model. This study extends the application of mass spectrometry (MS) to rapidly profile TCM-derived metabolites in vivo, which will help pharmacologists rapidly discover potent metabolites from a complex matrix.
A gene set enrichment analysis for the cancer hallmarks
Otília Menyhart, William Jayasekara Kothalawala, Balázs Győrffy
, Available online  , doi: 10.1016/j.jpha.2024.101065
Abstract(266) HTML Full Text PDF(14)
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The "hallmarks of cancer" concept provides a valuable framework for understanding fundamental organizing principles common to various cancers. However, without a consensus gene set for cancer hallmarks, data comparison and integration result in diverse biological interpretations across studies. Therefore, we aimed to form a consensus cancer hallmark gene set by merging data from available mapping resources and establishing a framework for mining these gene sets. By consolidating data from seven projects, 6,763 genes associated with ten cancer hallmarks were identified. A cancer hallmarks enrichment analysis was performed for prognostic genes associated with overall survival across twelve types of solid tumors. "Tissue invasion and metastasis" was most prominent in cancers of the stomach (P = 2.2×10-11), pancreas (P = 4.2×10-9), bladder (P = 3.3×10-8), and ovaries (P = 0.0007), aligning with their heightened potential to spread. "Sustained angiogenesis" was most prominent in squamous cell carcinomas of the lung (P = 2.5×10-7), while "genome instability" showed strong enrichment in lung adenocarcinomas (P = 1.5×10-8) and cancers of the liver (P = 5.5×10-10), pancreas (P = 2.1×10-5), and kidney (P = 0.018). Pancreatic cancers displayed the highest enrichment of hallmarks, emphasizing the disease's complexity, while in melanomas, and cancers of the liver, prostate, and kidney, a single hallmark was enriched among the prognostic markers of survival. Additionally, an online tool (www.cancerhallmarks.com) that allows the identification of cancer-associated hallmarks from new gene sets was established. In summary, our aim of establishing a consensus list of cancer hallmark genes was achieved. Furthermore, the analysis of survival-associated genes revealed a unique pattern of hallmark enrichment with potential pharmacological implications in different tumor types.
Pterostilbene: A natural neuroprotective stilbene with anti-Alzheimer’s disease properties
Songlan Gao, Honglei Zhang, Na Li, Lijuan Zhang, Zhe Zhu, Changlu Xu
, Available online  , doi: 10.1016/j.jpha.2024.101043
Abstract(74) HTML Full Text PDF(3)
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Alzheimer's disease (AD) is the leading cause of dementia, and no effective treatment has been developed for it thus far. Recently, the use of natural compounds in the treatment of neurodegenerative diseases has garnered significant attention owing to their minimal adverse reactions. Accordingly, the potential therapeutic effect of pterostilbene (PTS) on AD has been demonstrated in multiple in vivo and in vitro experiments. In this study, we systematically reviewed and summarized the results of these studies investigating the use of PTS for treating AD. Analysis of the literature revealed that PTS may play a role in AD treatment through various mechanisms, including anti-oxidative damage, anti-neuroinflammation, anti-apoptosis, cholinesterase activity inhibition, attenuation of β-amyloid deposition, and tau protein hyperphosphorylation. Moreover, PTS interferes with the progression of AD by regulating the activities of peroxisome proliferator-activated receptor alpha, monoamine oxidase B, Sirtuin-1, and phosphodiesterase 4A. Furthermore, to further elucidate the potential therapeutic mechanisms of PTS in AD, we employed network pharmacology and molecular docking technology to perform molecular docking of related proteins, and the obtained binding energies ranged from −2.83 kJ/mol to −5.14 kJ/mol, indicating that these proteins exhibit good binding ability with PTS. Network pharmacology analysis revealed multiple potential mechanisms of action for PTS in AD. In summary, by systematically collating and summarizing the relevant studies on the role of PTS in treatment of AD, it is anticipated that this will serve as a reference for the precise targeted prevention and treatment of AD, either using PTS or other developed drug interventions.
Radiotracer labelled thymohydroquinyl gallate capped gold nanoparticles as theranostic radiopharmaceutical for targeted antineoplastic and bioimaging
Munaza Batool, Batool Fatima, Dilshad Hussain, Rubaida Mahmood, Muhammad Imran, Saeed Akhter, Muhammad Saqib Khan, Saadat Majeed, Muhammad Najam-ul-Haq
, Available online  , doi: 10.1016/j.jpha.2024.100965
Abstract(154) HTML Full Text PDF(2)
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Thymoquinone (Tq) and gallic acid (GA) are known for counter-tumorigenic characteristics. GA inhibits cancer cell proliferation by interfering with many apoptotic signaling pathways, producing more reactive oxygen species (ROS), focusing on the cell cycle, and suppressing the expression of oncogenes and matrix metalloproteinases (MMPs). In this study, thymoquinone (after reducing to thymohydroquinone) and gallic acid are esterified to form thymohydroquinyl gallate (a prodrug). Thymohydroquinyl gallate (THQG) possesses enhanced antineoplastic efficacy and targeted delivery potential. The chemical and spectroscopic analysis confirms ester synthesis. Gold nanoparticles (AuNPs) are employed as nanocarriers due to their physicochemical and optical characteristics, biocompatibility, and low toxicity. As an efficient drug transporter, gold nanoparticles (AuNPs) shield conjugated drugs from enzymatic digestion. The prodrug acts as a reducing agent for Au metal atoms and is loaded onto it after reduction. The nano drug is radiolabeled with 99mTc and 131I to monitor the drug biodistribution in animals using a gamma camera and single-photon emission computerized tomography (SPECT). 131I is an antineoplastic that helps enhance the drug's efficiency. Chromatographic results reveal promising radiolabeling percentages. In vitro, drug release shows sustained release at pH 5.8. In vitro 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) cytotoxicity assay reveals drug potency on CAL 27 and MCF 7 cell lines.
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(725) HTML Full Text PDF(13)
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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)
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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.

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