Integrating deep learning and molecular dynamics simulations for FXR antagonist discovery.
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| Title: | Integrating deep learning and molecular dynamics simulations for FXR antagonist discovery. |
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| Authors: | Yang Y; Institute of Pharmaceutical Innovation, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China., Huang Y; Institute of Pharmaceutical Innovation, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China., Shen H; Institute of Pharmaceutical Innovation, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China., Wang D; Institute of Pharmaceutical Innovation, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China., Liu Z; School of Chemical Engineering, East China University of Science and Technology, Shanghai, 200237, China., Zhu W; SINOPEC-SK (Wuhan) Petrochemical Co., Ltd, Wuhan, 430082, China. zhuwei.zhsh@sinopec.com., Liu Q; Institute of Pharmaceutical Innovation, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China. lqing@wust.edu.cn.; Institute of Cardiovascular Diseases, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China. lqing@wust.edu.cn.; State Key Laboratory of Natural Medicines, Jiangsu Key Laboratory of Drug Discovery for Metabolic Diseases, Center of Drug Discovery, China Pharmaceutical University, Nanjing, 210009, China. lqing@wust.edu.cn. |
| Source: | Molecular diversity [Mol Divers] 2025 Aug; Vol. 29 (4), pp. 3391-3409. Date of Electronic Publication: 2025 Apr 02. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: ESCOM Science Publishers Country of Publication: Netherlands NLM ID: 9516534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-501X (Electronic) Linking ISSN: 13811991 NLM ISO Abbreviation: Mol Divers Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1573-501X |
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| DOI: | 10.1007/s11030-025-11145-2 |
