• 孙慧涌

    药物化学系 特聘副研究员
    领域:计算机辅助药物设计、人工智能
    联系电话:
    电子邮箱:huiyongsun@cpu.edu.cn
    办公室:江宁校区学院实验楼511室
    实验室:
  • 1、教育与工作经历
    2012/09-2015/06,苏州大学,功能纳米与软物资研究院,博士
    2015/07-2018/05,浙江大学,药学院,博士后/助理研究员
    2018/06至今,中国药科大学,药学院,特聘副研究员
    2、学术荣誉
    入选全球"Top 2%"科学家(2020)
    3、学术兼职
    (1) Journal of Chemical Information and Modeling青年编委(IF=6.162)
    (2) Frontiers in Molecular Biosciences副主编(Associate Editor for Biological Modeling and Simulation),主持“Free Energy Calculation: Current Paradigms and Applications for Drug Discovery”特刊两期(IF=6.113)
    (3) Molecules特刊编委,主持“Drug Design with Advanced Computational Strategies and Artificial Intelligence”特刊一期(IF=4.927)
    1.基于人工智能技术的药物设计
    2.基于分子模拟技术的药物发现与作用机制研究
    1. 科研项目
    (1).项目名称:新型抗耐药ALK抑制剂的分子设计及药理活性初步评价,国家自然基金青年项目,项目编号:81603031,资助金额:17.3万元,起止时间:2017.01-2019.12,已结题,主持
    (2).项目名称:层级式耐药性分析策略在抗耐药ALK抑制剂发现中的应用,中国博士后第9批特别资助,项目编号:2016T90550,资助金额:15万元,起止时间:2016.06-2017.06,已结题,主持
    (3).项目名称:基于多维度自由能计算策略的新型ALK抗耐药抑制剂设计,中国博士后第58批面上二等资助,项目编号:2015M581953,资助金额:5万元,起止时间:2015.12-2017.06,已结题,主持
    (4).项目名称:基于创新算法的FXR-Caspase8 First-in-Class稳定剂设计,中国药科大学青年英才突破性成果培育计划,项目编号:131810011/1132010013,资助金额:42万元,起止时间:2019.01-2021.12,已结题,主持
    2. 成果概述
    课题组长期致力于计算机(人工智能)辅助药物设计研究(CADD/AIDD),在重要靶点的药物设计(如难靶靶点药物设计)、高精度虚拟筛选策略(包括基于终点式自由能计算和加强采样模拟的药物-靶标相互作用表征)以及人工智能算法研究方面(包括基于先进AI架构的药物-靶标相互作用识别,分子生成等)取得系列成果。近年来,孙慧涌博士共发表SCI论文90余篇,论文引用总量超过6000次(包括多篇“单篇引用”超过500次论文,H因子为34),相关第一或通讯作者论文发表于Chemical Reviews、Cell Reports Physical Science、JACS Au、Research、Journal of Medicinal Chemistry、Briefings in Bioinformatics、Journal of Chemical Theory and Computation、British Journal of Pharmacology、Analytical Chemistry等行业重要期刊中,担任Journal of Chemical Information and Modeling青年编委(IF=6.162)、Frontiers in Molecular Biosciences副主编(Associate Editor for Biological Modeling and Simulation, IF=6.113),入选全球"Top 2%"科学家(2020),详情请参阅https://www.researchgate.net/profile/Huiyong-Sun-2。
    1.Qinghua Wang, Zhe Wang, Qirui Deng, Sutong Xiang, Rongfan Tang, Yang Yu, Tingjun Hou*, Haiping Hao*, Huiyong Sun*, Discriminating functional and non-functional nuclear-receptor ligands with a conformational selection-inspired machine-learning algorithm, Cell Reports Physical Science, 2023, Accepted.
    2.Rongfan Tang, Zhe Wang, Sutong Xiang, Lingling Wang, Yang Yu, Qinghua Wang, Qirui Deng, Tingjun Hou*, Huiyong Sun*, Uncovering the kinetic characteristics and degradation preference of PROTAC systems with advanced theoretical analyses, JACS Au, 2023, Accepted.
    3.Yang Yu, Zhe Wang, Lingling Wang, Qinghua Wang, Rongfan Tang, Sutong Xiang, Qirui Deng, Tingjun Hou*, Huiyong Sun*, Deciphering the Shared and Specific Drug Resistance Mechanisms of Anaplastic Lymphoma Kinase via Binding Free Energy Computation, Research, 2023, Accepted. (IF=11.036)
    4.Lingling Wang, Lei Xu, Zhe Wang, Tingjun Hou*, Haiping Hao*, Huiyong Sun*, Cooperation of Structural Motifs Controls Drug Selectivity in Cyclin-Dependent Kinases: An Advanced Theoretical Analysis, Briefings in Bioinformatics, 2023, 24, bbac544. (IF=13.994)
    5.Qinghua Wang, Zhe Wang, Sheng Tian, Lingling Wang, Rongfan Tang, Yang Yu, Jingxuan Ge, Tingjun Hou*, Haiping Hao*, Huiyong Sun*, Determination of Molecule Category of Ligands Targeting the Ligand-Binding Pocket of Nuclear Receptors with Structural Elucidation and Machine Learning, Journal of Chemical Information and Modeling, 2022, 62, 3993-4007. (IF=6.162)
    6.Rongfan Tang, Pengcheng Chen, Zhe Wang, Lingling Wang, Haiping Hao*, Tingjun Hou*, Huiyong Sun*, Characterizing the Stabilization Effects of Stabilizers in Protein-Protein Systems with End-Point Binding Free Energy Calculations, Briefings in Bioinformatics, 2022, 23, bbac127. (IF=13.994)
    7.Yang Yu, Zhe Wang, Lingling Wang, Sheng Tian, Tingjun Hou*, Huiyong Sun*, Predicting the Mutation Effects of Protein-Ligand Interactions via End-Point Binding Free Energy Calculations: Strategies and Analyses, Journal of Cheminformatics, 2022, 14, 56. (IF=8.489)
    8.Jike Wang, Dongsheng Cao, Cunchen Tang, Lei Xu, Qiaojun He, Bo Yang, Xi Chen*, Huiyong Sun*, Tingjun Hou*, DeepAtomicCharge: A New Graph-Convolution-Network-based Architecture for Accurate Prediction of Atomic Charges, Briefings in Bioinformatics, 2021, 22, bbaa183. (IF=13.994)
    9.Jike Wang, Dongsheng Cao, Cunchen Tang, Xi Chen*, Huiyong Sun*, Tingjun Hou*, Fast and Accurate Prediction of Partial Charges Using Atom-Path-Descriptor-based Machine Learning, Bioinformatics, 2020, 36, 4721-4728. (IF=6.937)
    10.Ercheng Wang#, Huiyong Sun#, Junmei Wang, Zhe Wang, Hui Liu, John Z.H. Zhang*, Tingjun Hou*, End-Point binding free energy calculation with MM/PBSA and MM/GBSA: strategies and applications in drug design, Chemical Reviews, 2019, 119, 16, 9478-9508. (IF=52.758)