基本信息：
蒋德军，男，博士,韩漫
特聘副教授,硕士研究生导师,中共党员。1994年10月生，重庆开州人。2017毕业于中国药科大学,获学士学位，2022年毕业于浙江大学，获博士学位。蒋德军博士长期致力于人工智能药学和化学信息学等交叉领域的研究。近五年在Nature Machine Intelligence、NatureComputationalScience、NatureCommunications、Chemical Science、Journal of Medicinal Chemistry和Research等国际高水平期刊发表论文40余篇,其中以第一作者或者通讯作者（含共同）在Chemical Science、Journal of Medicinal Chemistry、Research和Journal of Chemical Theory and Computation等权威期刊发表论文逾20篇。其研究成果广受学术界关注，其中两篇第一作者研究论文被引用分别逾700次（J Cheminform 13, 12 (2021)）与250次（J. Med. Chem. 2021, 64, 24, 18209–18232），Google Scholar统计总被引逾2616余次，H-index指数23。蒋德军博士同时担任NatureCommunications、JournalofCheminformatics、Briefings in Bioinformatics等国际知名期刊审稿人，积极参与国际学术共同体建设与同行评议工作。主持2025重大新药创制子课题、国家自然科学基金青年项目、中国博士后科学基金面上项目（二等）、湖南省自然科学基金青年项目等多项科研项目，并成功入选2023年国家资助博士后研究人员计划（B档）。曾荣获“浙江大学优秀研究生”、“三好研究生”、“优秀毕业研究生”等多项荣誉称号。
研究方向：
1.人工智能药学
2.计算机辅助药物设计
教育与工作经历：
2024-07至今,韩漫
，韩漫
，特聘副教授，硕士研究生导师
2022-06至2024-07，浙江大学智能创新药物研究院，博士后/助理研究员(合作导师：侯廷军教授)
2020-09至2022-06,浙江大学,计算机技术,博士(导师：吴健教授、侯廷军教授)
2017-09至2020-06,浙江大学,药学,其他
2013-09至2017-06,中国药科大学,信息管理与信息系统,学士
科研项目与资助：
（1）国家自然基金青年项目，资助金额：30万元，起止时间：2024.01 – 2026.12，主持
（2）中国博士后面上基金（二等），资助金额：8万元，起止时间：2022.10 – 2024.10，主持
（3）2023年国家资助博士后研究人员计划（B档），36万元，主持，起止时间：2022.10 – 2024.10
（4）湖南省青年基金项目，5万元，2025.06– 2028.06，主持
（5）2025“创新药物研发”国家科技重大专项（子课题负责人），140万元，2026.01–2028.12， 主持
谷歌学术链接：
//scholar.google.com/citations?user=B1J94LwAAAAJ&hl=zh-CN
联系方式:[email protected]
近5年代表性科研论文：
1.Jiang, D.;Zhao, H.; Du, H.; Deng, Y.; Wu, Z.; Wang, J.; Zeng, Y.; Zhang, H.; Wang, X.; Wu, J.; Hsieh, C. Y.; Hou, T., How Good Are Current Docking Programs at Nucleic Acid–Ligand Docking? A Comprehensive Evaluation.Journal of Chemical Theory and Computation2023, 19, 5633-5647.(JCR1区,中科院1区)
2.Jiang, D.;Ye, Z.; Hsieh, C.-Y.; Yang, Z.; Zhang, X.; Kang, Y.; Du, H.; Wu, Z.; Wang, J.; Zeng, Y.; Zhang, H.; Wang, X.; Wang, M.; Yao, X.; Zhang, S.; Wu, J.; Hou, T. MetalProGNet: a structure-based deep graph model for metalloprotein–ligand interaction predictions.Chemical Science2023, 14, 2054-2069.(JCR1区,中科院1区，NatureIndex期刊)
3.Jiang, D.#; Sun, H.#; Wang, J.#; Hsieh, C.-Y.; Li, Y.; Wu, Z.; Cao, D.; Wu, J.; Hou, T., Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning.Briefings in Bioinformatics2022, 23, bbab597.(JCR1区,中科院1区)
4. Du, H.#;Jiang, D.#; Gao, J.; Zhang, X.; Jiang, L.; Zeng, Y.; Wu, Z.; Shen, C.; Xu, L.; Cao, D., Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network.Research2022.(JCR1区,中科院1区)
5.Wu, Z.#;Jiang, D.#; Hsieh, C.-Y.; Chen, G.; Liao, B.; Cao, D.; Hou, T., Hyperbolic relational graph convolution networks plus: a simple but highly efficient QSAR-modeling method.Briefings in Bioinformatics2021, 22, bbab112.(JCR1区,中科院1区)
6.Jiang, D.#; Wu, Z.#; Hsieh, C.-Y.; Chen, G.; Liao, B.; Wang, Z.; Shen, C.; Cao, D.; Wu, J.; Hou, T., Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models.Journal of cheminformatics2021, 13, 1-23.(JCR1区,中科院2区,谷歌学术他引700次，截至2025.12)
7.Jiang, D.;Hsieh, C.-Y.; Wu, Z.; Kang, Y.; Wang, J.; Wang, E.; Liao, B.; Shen, C.; Xu, L.; Wu, J.; Cao, D.; Hou, T., InteractionGraphNet: a novel and efficient deep graph representation learning framework for accurate protein–ligand interaction predictions.Journal of medicinal chemistry2021, 64, 18209-18232.(JCR1区,中科院1区,IF5=7.2,谷歌学术他引248次，截至2025.12)
8.Jiang, D.; Lei, T.; Wang, Z.; Shen, C.; Cao, D.; Hou, T., ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning.Journal of Cheminformatics2020, 12, 1-26.(JCR1区,中科院2区)
9. Hongyan Du#;Dejun Jiang#; Haotian Zhang; Zhenxing Wu; Junbo Gao; Xujun Zhang; Xiaorui Wang; Yafeng Deng; Yu Kang; Dan Li; Peichen Pan; Chang-Yu Hsieh; Tingjun Hou. A Flexible Data-Free Framework for Structure Based De Novo Drug Design with ReinforcementLearning.Chem. Sci., 2023,14, 12166-12181(JCR1区,中科院1区,NatureIndex期刊)
10.Dejun Jiang;Hongyan Du; Huifeng Zhao; Yafeng Deng; Zhenxing Wu; Jike Wang; Yundian Zeng; Haotian Zhang; Xiaorui Wang; Ercheng Wang; Tingjun Hou; Chang-Yu Hsieh. Assessing the Performance of MM/PBSA and MM/GBSA Methods. 10. Prediction Reliability of Binding Affinities and Binding Poses for RNA-ligand Complexes.Physical Chemistry Chemical Physics.2024,26, 10323-10335.(JCR1区)
11.Jingxuan Ge#,Dejun Jiang#,Huiyong Sun#,YuKang, Peichen Pan, Yafeng Deng, Chang-Yu Hsieh, Tingjun Hou.Deep-learning-based prediction framework for protein-peptide interactions with structure generation pipeline.Cell Reports Physical ScienceVolume 5, Issue 6, 101980, June 19, 2024.(JCR1区,中科院2区)
12.Huifeng Zhao#,Dejun Jiang#, Chao Shen,Jintu Zhang, Xujun Zhang, Xiaorui Wang, Dou Nie, Yu Kang, Tingjun Hou. Comprehensive Evaluation of Ten Docking Programs on a Diverse Set of Protein-cyclic Peptide Complexes.Journal of Chemical Information and Modeling.2024, 64, 6, 2112–2124.(JCR1区)
13.Nanqi Hong#，Dejun Jiang#，TransfIGN: A Structure-Based Deep Learning Method for Modeling the Interaction between HLA-A*02:01 and Antigen Peptides.Journal of Chemical Information and Modeling2024, 64, 13, 5016–5027. (JCR1区)
14. Cuiyu Li, Hongyan Du, Chengwei Zhang, Wanying Huang, Xujun Zhang, Tianyue Wang,Dejun Jiang*, Tingjun Hou*, and Ercheng Wang*.Comprehensive Evaluation of End-Point Free Energy Methods in DNA–Ligand Interaction Predictions.Journal of Chemical Information and Modeling2025 65 (4), 2014-2025.(JCR1区)
15.Kaimo Yang#,Dejun Jiang#, Qirui Deng, Sutong Xiang, Jingxuan Ge, Kexin Xu, Zhiliang Jiang, Zihao Wang, Chen Yin, Youqiao Qian, Tingjun Hou, Huiyong Sun.A Unified Deep Graph Model for Identifying the Molecular Categories of Ligands Targeting Nuclear Receptors.J. Chem. Inf. Model. 2025, 65, 11, 5481–5494(JCR1区)
16.Jian-Wang Li, Ke-yi Liu, You-Chao Deng, Shao-Hua Shi, Xiang-Zheng Fu, Yue-Ping Jiang, Jing Fang,De-Jun Jiang*, Shao Liu*, Dong-Sheng Cao*.Uncertainty-Aware Deep Learning Modeling and Structural Feature Insights for Nephrotoxicity Prediction.J. Chem. Inf. Model.(JCR1区)
17.Kun Li, Jiacai Yi, Qing Ye, Xixi Yang, Long Yu, YouChao Deng, Chengkun Wu, Tingjun Hou*,Dejun Jiang*, Dongsheng Cao*. A fused deep learning approach to transform drug repositioning.Commun Chem8, 334 (2025).(中科院1区)
18. Yue Li, Jiacai Yi, Hui Li, Kun Li, Youchao Deng, Chengkun Wu, Xiangzheng Fu,Dejun Jiang*, Dongsheng Cao*. Decoding the Limits of Deep Learning in Drug Discovery: Benchmarking AI-Driven Molecular Docking.Chem. Sci., 2025, 16, 17374-17390（中科院1区，NI指数）
19.Dejun Jiang#, Huifeng Zhao#, Hongyan Du#, Yu Kang, Peichen Pan, Zhenxing Wu, Yundian Zeng, Odin Zhang, Xiaorui Wang, Jike Wang, YuanSheng Huang, Yihao Zhao, Chang-Yu Hsieh*, Dongsheng Cao*, Huiyong Sun*, Tingjun Hou*. Harnessing Deep Statistical Potential for Biophysical Scoring of Protein-peptide Interactions.Acta Pharmacol Sin (2025).//doi.org/10.1038/s41401-025-01659-8（中科院2区）
