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李卫华 教授 博士生导师
Email：whli.at.ecust.edu.cn（用@替换.at.）
【个人简介】
1999年毕业于安徽师范大学化学系，获学士学位；2002年毕业于华南师范大学化学系，获硕士学位；2005年毕业于中国科学院上海药物研究所，获博士学位。2005年9月至2007年6月在华东理工大学药学院从事博士后研究；2007年7月至2009年6月获日本学术振兴会（JSPS）奖学金，在日本千叶大学药学部从事博士后研究。2009年9月到华东理工大学药学院工作，历任副研究员，教授。
【研究方向】
1）蛋白质/酶的计算模拟和药物设计
2）人工智能方法在药物发现和设计中的应用
主要从事蛋白质/酶的计算模拟和计算机辅助药物设计研究工作。运用计算模拟和人工智能技术，围绕P450酶介导的药物代谢、化合物ADMET性质预测、核受体的药物发现和设计等方面开展研究。研究工作先后发表于J Chem Inf Model, J Chem Theory Comput, Chem Eur J, Mol Pharm, Chem Res Toxicol, Drug Metab Dispos等期刊。作为主持人先后承担国家自然科学基金、上海市自然科学基金等科研项目；作为项目骨干参与国家重点研发计划课题和新药创制重大专项课题。
【近期主要论文】
• Xiang Li, Meiling Zhan, Jiaojiao Fang, Guixia Liu, Yun Tang*, and Weihua Li*. MMPK: A multimodal deep learning framework to predict human oral pharmacokinetic parameters. J. Med. Chem. 2025,68, 16678−16690.
• Changda Gong, Jiaojiao Fang, Yan Tang, Guixia Liu, Yun Tang*, and Weihua Li*. SGEDiff: a subgraph-enriched diffusion model for structure-based 3D molecular generation. J. Cheminform. 2025, 17, 175.
• Yan Tang, Jiaojiao Fang, Guixia Liu, Yun Tang, and Weihua Li*. Computational insights into the regioselective hydroxylation of nirmatrelvir metabolized by cytochrome P450 3A4. J. Chem. Inf. Model. 2025, 65, 13346−13359.
• Yanjun Feng, Changda Gong, Jieyu Zhu, Guixia Liu, Yun Tang*, and Weihua Li*. Unraveling the ligand-binding sites of CYP3A4 by molecular dynamics simulations with solvent probes. J. Chem. Inf. Model. 2024, 64, 3451−3464.
• Jiaojiao Fang, Yan Tang, Changda Gong, Zejun Huang, Yanjun Feng, Guixia Liu, Yun Tang, and Weihua Li*. Prediction of cytochrome P450 substrates using the explainable multitask deep learning models. Chem. Res. Toxicol. 2024, 37, 1535−1548.
• Yanjun Feng, Changda Gong, Jieyu Zhu, Guixia Liu, Yun Tang*, and Weihua Li*. Prediction of sites of metabolism of CYP3A4 substrates utilizing docking-derived geometric features. J. Chem. Inf. Model. 2023, 63, 4158-4169.
• Minjie Xu, Zhou Lu, Zengrui Wu, Minyan Gui, Guixia Liu, Yun Tang*, and Weihua Li*. Development of in silico models for predicting potential time-dependent inhibitors of cytochrome P450 3A4. Mol. Pharmaceut. 2023, 20, 194-205.
• Longqiang Li, Zhou Lu, Guixia Liu, Yun Tang, and Weihua Li*. Machine learning models to predict cytochrome P450 2B6 inhibitors and substrates. Chem. Res. Toxicol. 2023, 36, 1332-1344.
• Longqiang Li, Zhou Lu, Guixia Liu, Yun Tang, and Weihua Li*. In silico prediction of human and rat liver microsomal stability via machine learning methods. Chem. Res. Toxicol. 2022, 35, 1614−1624.
• Minjie Xu, Hongbin Yang, Guixia Liu, Yun Tang*, and Weihua Li*. In silico prediction of chemical aquatic toxicity by multiple machine learning and deep learning approaches. J. Appl. Toxicol. 2022, 42,1766- 1776.
• Xiaoxiao Zhang, Piaopiao Zhao, Zhiyuan Wang, Xuan Xu, Guixia Liu, Yun Tang, and Weihua Li*. In silico prediction of CYP2C8 inhibition with machine learning methods. Chem. Res. Toxicol.2021, 34, 1850-1859.
• Xiaoxiao Zhang, Minjie Xu, Zengrui Wu, Guixia Liu, Yun Tang, and Weihua Li*. Assessment of CYP2C9 structural models for site of metabolism prediction. ChemMedChem 2021, 16, 1754-1763.
• Junhao Li, Yue Chen, Yun Tang, Weihua Li*, and Yaoquan Tu*. Homotropic cooperativity of midazolam metabolism by cytochrome P450 3A4: Insight from computational studies. J. Chem. Inf. Model. 2021, 61, 2418-2426.
• Junhao Li, Yang Zhou, Yun Tang, Weihua Li*, and Yaoquan Tu*. Dissecting the structural plasticity and dynamics of cytochrome P450 2B4 by molecular dynamics simulations. J. Chem. Inf. Model. 2020, 60, 5026-5035.
• Yue Chen, Junhao Li, Zengrui Wu, Guixia Liu, Honglin Li, Yun Tang*, and Weihua Li*. Computational insight into the allosteric activation mechanism of farnesoid X receptor. J. Chem. Inf. Model. 2020, 60, 1540-1550.
• Junhao Li, Yun Tang, Weihua Li*, and Yaoquan Tu*. Mechanistic insights into the regio- and stereoselectivities of testosterone and dihydrotestosterone hydroxylation catalyzed by CYP3A4 and CYP19A1. Chem. Eur. J. 2020, 26, 6214-6223.
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