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Xingang Liu, Hao Yang, Xinyu Liu, Minjie Mou, Jie Liu, Wenying Yan, Tianle Niu, Ziyang Zhang, He Shi, Xiangdong Su, Xuedong Li, Yang Zhang, Qingzhong Jia. Discovery of Selective HDAC6 Inhibitors Driven by Artificial Intelligence and Molecular Dynamics Simulation Approaches[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2025.101338
Citation: Xingang Liu, Hao Yang, Xinyu Liu, Minjie Mou, Jie Liu, Wenying Yan, Tianle Niu, Ziyang Zhang, He Shi, Xiangdong Su, Xuedong Li, Yang Zhang, Qingzhong Jia. Discovery of Selective HDAC6 Inhibitors Driven by Artificial Intelligence and Molecular Dynamics Simulation Approaches[J]. Journal of Pharmaceutical Analysis. doi: 10.1016/j.jpha.2025.101338

Discovery of Selective HDAC6 Inhibitors Driven by Artificial Intelligence and Molecular Dynamics Simulation Approaches

doi: 10.1016/j.jpha.2025.101338
Funds:

This research was funded by Central Guidance on Local Science and Technology Development Fund of Hebei Province (226Z2605G), the Key Project from Hebei Provincial Department of Science and Technology (21372601D), Graduate Student Innovation Grant Program of Hebei Medical University (XCXZZB202303), Science Research Project of Hebei Education Department (BJ2025046, CYZD202501), Program for Young Scientists in the Field of Natural Science of Hebei Medical University (CYCZ2023010, CYCZ2023011, CYQD2021011, CYQD2021015 and CYQD2023012), Traditional Chinese Medicine Administration Project of Hebei Province (2025427), National Natural Science Foundation of China (32100771), and the Hebei Provincial Medical Science Research Project Plan (20240241 and 20220200), Shijiazhuang Science and Technology Bureau (241200487A, 07202204).

  • Received Date: Nov. 04, 2024
  • Accepted Date: May 06, 2025
  • Rev Recd Date: Mar. 21, 2025
  • Available Online: May 14, 2025
  • Increasing evidence showed that HDAC6 dysfunction is directly associated with the onset and progression of various diseases, especially cancers, making the development of HDAC6-targeted anti-tumor agents a research hotspot. In this study, artificial intelligence (AI) technology and molecular simulation strategies were fully integrated to construct an efficient and precise drug screening pipeline, which combined Voting strategy based on compound-protein interaction (CPI) prediction models, cascade molecular docking, and molecular dynamic (MD) simulations. The biological potential of the screened compounds was further evaluated through enzymatic and cellular activity assays. Among the identified compounds, Cmpd.18 exhibited more potent HDAC6 enzyme inhibitory activity (IC50 = 5.41 nM) than that of Tubastatin A ( TubA ) (IC50 = 15.11 nM), along with a favorable subtype selectivity profile (selectivity index ≈ 117.23 for HDAC1), which was further verified by the western blot analysis. Additionally, Cmpd.18 induced G2/M phase arrest and promoted apoptosis in HCT-116 cells, exerting desirable antiproliferative activity (IC50 = 2.59 μM). Furthermore, based on long-term MD simulation trajectory, the key residues facilitating Cmpd.18 ’s binding were identified by decomposition free energy analysis, thereby elucidating its binding mechanism. Moreover, the representative conformation analysis also indicated that Cmpd.18 could stably bind to the active pocket in an effective conformation, thus demonstrating the potential for in-depth research of the 2-(2-phenoxyethyl)pyridazin-3(2H)-one scaffold.
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