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卞月珉

创建时间:  2024-04-07  庄薪荣   浏览次数:   返回

个人介绍:

卞月珉,上海大学特聘教授,博士生导师,国家级高层次青年人才,上海市海外高层次人才;2015年本科毕业于中国药科大学,2020年博士毕业于美国匹兹堡大学,20211-20242月在美国麻省理工和哈佛大学布罗德研究所从事新药研发工作,担任资深计算科学家;长期致力于人工智能药物发现相关研究,通过开发并整合机器学习与深度学习算法,计算化学与计算生物学策略手段,加速临床前早期药物发现;近五年,发表包括Nature, Cell在内的通讯/第一/共一SCI论文及专著15篇,H因子12,累计影响因子超过196;主持国家级高层次海外人才基金项目、国家自然科学基金青年科学基金项目、上海市高层次海外人才基金项目等;现为英国国家研究与创新署UKRI、智利国家研究与发展署ANID基金评审外籍专家,BMC Pharmacology and Toxicology杂志客座编辑,Nature CommunicationsBriefings in Bioinformatics等杂志审稿人。

主要研究领域:

人工智能药物设计,计算化学,计算生物学,药物化学,靶向药物开发

专注于人工智能和药物发现的跨学科交叉,特别是针对小分子药物的智能筛选与优化,初步构建了聚焦于新型靶标确证与苗头发现的人工智能药物设计平台。

1)以计算为桥梁完成癌症新靶点SHOC2-MRAS-PP1C全酶的结构解析与功能分析,为RAS病理相关癌症治疗开创全新药物靶标(Nature 2022);

2)将大分子生物计算与结构生物学相融合,揭示HSV Polymerase耐药性突变的动态结构性解释,为针对耐药病毒株的原创药物发现提供支撑(Cell 2024);

3)实现超高通量虚拟筛选和生成式配体结构从头设计,结合药物化学分子合成,针对新型靶点开展苗头发现与先导优化。

科研、教学项目:

1. 国家级高层次人才青年项目,人工智能创新药物设计,2025/01-2027/12,在研,主持

2. 国家自然科学基金青年项目,基于生成式人工智能设计SHOC2全酶抑制剂并构建苗头分子发现平台,2025/01-2027/12,在研,主持

3. 上海市海外高层次人才项目,2024/01-2027/06, 在研,主持

4. 上海大学研究生院卓越工程师课程建设项目, 人工智能药物发现,2024,在研,主持

5. 上海大学地方高水平大学一流研究生培养质量提升项目,人工智能药物发现,2024,在研,主持

代表性学术成果:

论文(最具代表性)

1. Sundaresh Shankar*, Junhua Pan*, Pan Yang*, Yuemin Bian*, Gabor Oroszlan, Zishuo Yu, Purba Mukherjee, David J. Filman, James M. Hogle, Mrinal Shekhar, Donald M. Coen, Jonathan Abraham. Viral DNA polymerase structures reveal mechanisms of antiviral drug resistance. Cell, 187(20), 5572-5586 (2024). (IF = 64.5共同第一作者)

2. Jason J. Kwon*, Behnoush Hajian*, Yuemin Bian*, Lucy C. Young*, Alvaro J. Amor, James R. Fuller, Cara V. Fraley, Abbey M. Sykes, Jonathan So, Joshua Pan, Laura Baker, Sun Joo Lee, Douglas B. Wheeler, David L. Mayhew, Nicole S. Persky, Xiaoping Yang, David E. Root, Anthony M. Barsotti, Andrew W. Stamford, Charles K. Perry, Alex Burgin, Frank McCormick, Christopher T. Lemke, William C. Hahn, Andrew J. Aguirre. Structure-function analysis of the SHOC2-MRAS-PP1C holophosphatase complex. Nature 609, 408–415 (2022). (IF = 69.5共同第一作者)

3. Yue-min Bian, Xi-bing He, Yan-kang Jing, Li-rong Wang, Jun-mei Wang, Xiang-Qun Xie. Computational systems pharmacology analysis of cannabidiol: a combination of chemogenomics-knowledgebase network analysis and integrated in silico modeling and simulation. Acta Pharmacologica Sinica, 40.3 (2019): 374. (IF = 8.2,第一作者)

4. Yuemin Bian, Jaden Jungho Jun, Jacob Cuyler, Xiang-Qun Xie. Covalent allosteric modulation: an emerging strategy for GPCR drug discovery, European Journal of Medicinal Chemistry (2020). 112690. (IF = 7.1,第一作者)

5. Yuemin Bian, Xiang-Qun Xie. Artificial Intelligent Deep Learning Molecular Generative Modeling of Scaffold-Focused and Cannabinoid CB2 Target-Specific Small-Molecule Sublibraries. Cells 11.5 (2022): 915. (IF = 7.6,第一作者)

6. Yuemin Bian, Jason J Kwon, Cong Liu, Enrico Margiotta, Mrinal Shekhar, Alexandra E Gould. Target-driven machine learning-enabled virtual screening (TAME-VS) platform for early-stage hit identification. Frontiers in Molecular Biosciences (2023), 10, 174. (IF = 6.1,第一作者)

7. Yuemin Bian, Junmei Wang, Jaden Jungho Jun, Xiang-Qun Xie. Deep convolutional generative adversarial network (dcGAN) models for the screening and design of small molecules targeting cannabinoid receptors. Molecular Pharmaceutics (2019), 16 (11), 4451-4460 (IF = 5.4,第一作者)

8. Yuemin Bian, Yankang Jing, Lirong Wang, Shifan Ma, Jaden Jungho Jun, Xiang-Qun Xie. Prediction of orthosteric and allosteric regulations on cannabinoid receptors using supervised machine learning classifiers. Molecular Pharmaceutics (2019), 16, 6, 2605-2615 (IF = 5.4,第一作者)

9. Yuemin Bian, Xiang-Qun Xie. Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications. The AAPS Journal, (2018), 20(3): 59. (IF = 3.6,第一作者)

10. Yuemin Bian, Zhiwei Feng, Peng Yang, Xiang-Qun Xie. Integrated in silico fragment-based drug design: case study with allosteric modulators on metabotropic glutamate receptor 5. The AAPS Journal, (2017), 19(4): 1235-1248. (IF = 3.6,第一作者)

参编著作

Bian, Y., Hou, G., Xie, XQ. (2023). Artificial Intelligence Generative Chemistry Design of Target-Specific Scaffold-Focused Small Molecule Drug Libraries. In: Jagadeesh, G., Balakumar, P., Senatore, F. (eds) The Quintessence of Basic and Clinical Research and Scientific Publishing. Springer, Singapore.

社会学术兼职:

英国国家研究与创新署UK Research and Innovation (UKRI) 外籍基金评审

智利国家研究与发展部National Research and Development Agency (ANID) of the Ministry of Science, Technology, Knowledge and Innovation of Chile 外籍基金评审

BMC Pharmacology and Toxicology杂志编委

Nature CommunicationsBriefings in Bioinformatics等杂志审稿人






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