方坚松
近期热点
资料介绍
个人简历
博士期间从事基于机器学习的抗老年痴呆药物发现研究,入职广中医以来致力于运用系统药理学及人工智能技术(如深度学习神经网络)在抗肿瘤与老年痴呆药物(老药与天然产物)与靶标发现、中药毒性机理及精准医学等方面的交叉应用研究。自2011年以来,在Nat Commun,Cell Chem Biol,Brief Bioinform,Mol Ther Nucleic Acids等期刊发表SCI论文70余篇,论文引用次数850余次(google scholar,H因子18),包括第一作者或通讯作者26篇(累计影响因子大于100,中科院二区以上文章17篇),其中cell子刊一篇(Cell Chem Biol 2019, IF=6.8),中科院一区3篇,包括生物信息学旗舰杂志Brief Bioinform (IF=9.1)、药学期刊Acta Pharm Sin B (IF=5.8)及药化期刊Eur J Med Chem。此外,项目申请人在化学信息学领域具有扎实的学术积累,目前已在美国化学会旗下的化学信息学领域top期刊J Chem Inf Model(中科院二区)发表研究性论文六篇(第一作者或共同通讯作者)。 教育背景2012/09 - 2015/07,北京协和医学院(清华大学医学部),药理学,博士 2009/09 - 2012/07,中山大学,药物化学,硕士 2005/09 - 2009/07,广东药科大学,药学,学士 工作经历2015/09~2017.12,广州中医药大学,临床药理研究所,助理研究员2018/01~至今,广州中医药大学,临床药理研究所,副研究员2018/12~2019.12,美国克利夫兰医学中心,Lerner Research Insitute,国家留学基金委公派博士后 主要荣誉2019年中国药理学会青年药理学家奖 项目主持:(1) 国家自然基金青年基金项目(81603318,17万):基于网络多靶标探讨补肾益智方抗AD药效物质基础及作用机制。(2) 广东省教育厅普通高校特色创新类项目(A1-AFD018171Z1306,10万):基于系统药理学的中药有效成分药物靶标识别及其功能验证研究。(3) 高水平大学面上项目(A1-AFD018171Z11027,20万):中草药-靶标数据库构建及其应用研究。(4) 高水平大学青年科研培育项目(2019QNPY05,30万):基于网络距离邻近法预测中药天然产物抗三阴性乳腺癌活性及作用机制研究。(5) 一流学科高水平大学建设特色培育团队项目(XKP2019005,60万):基于系统药理学的抗肿瘤活性天然产物发现。(6) 广州中医药大学青年英才(20万)。研究领域
"中药学"近期论文
(1) Hong H#, Mo Y#, Li D#, Xu Z, Liao Y, Yin P, Liu X, Xia Y, Fang J*, Wang Q* and Fang S*. Aberrant Expression Profiles of lncRNAs and Their Associated Nearby Coding Genes in the Hippocampus of the SAMP8 Mouse Model with AD. Mol Ther Nucleic Acids. 2020; 20:140-154. (2) Luo Y#, Li D#, Liao Y#, Cai C, Wu Q, Ke H, Liu X, Li H, Hong H, Xu Y, Wang Q*, Fang J*, Fang S*. Systems Pharmacology Approach to Investigate the Mechanism of Kai-Xin-San in Alzheimer’s Disease. Frontiers in Pharmacology. 2020; 11: 381. (3) Liu Z#, Cai C#, Du J#, Liu B, Cui L, Fan X, Fang J*, Xie L*.TCMIO: A Comprehensive Database of Traditional Chinese Medicine on Immuno-Oncology. Frontiers in Pharmacology. 2020; 11: 439. (4) Huang Y, Fang J*, Lu W*, Wang Z, Wang Q, Hou Y, Jiang X, Reizes O, Lathia J, Nussinov R, Eng C, Cheng F*. A systems pharmacology approach uncovers wogonoside as a novel angiogenesis inhibitor of triple-negative breast cancer by targeting Hedgehog signaling, Cell Chem Biol, 2019; 26: 1-16. (5) Guo P, Cai C, Wu X, Fan , Huang W, Zhang Y*, Fang J*. An Insight Into the Molecular Mechanism of Berberine Towards Multiple Cancer Types Through Systems Pharmacology. Front Pharmacol 2019;10:857. (6) Cai C, Guo P, Zhou Y, Zhou J, Wang Q, Zhang F, Fang J*, Cheng F*. Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity. J Chem Inf Model 2019;59(3):1073-1084.(7) Fang J, Cai C, Chai Y, Zhou J, Huang Y, Gao L, Wang Q, Cheng F*. Quantitative and systems pharmacology 4. Network-based analysis of drug pleiotropy on coronary artery disease. Eur J Med Chem 2019; 161:192-204. (8) Wu Q#, Cai C#, Guo P, Chen M, Wu X, Zhou J, Luo Y, Zou Y, Liu AL, Wang Q, Kuang Z*, Fang J*. In Silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine. Front Pharmacol 2019;10:458. (9) Wu Q, Ke H, Li D, Wang Q, Fang J*, Zhou J*. Recent Progress in Machine Learning-based Prediction of Peptide Activity for Drug Discovery. Curr Top Med Chem 2019;19(1):4-16. (10) Wang L#, Fang J#, Jiang H, Wang Q, Xue S, Li Z, Liu R. 7-pyrrolidinethoxy-4'-methoxyisoflavone prevents amyloid β–induced injury by regulating histamine H3 receptor-mediated cAMP/CREB and AKT/GSK3β pathways. Frontiers in neuroscience 2019; 13, 334(11) Fang J, Liu C, Wang Q, Lin P, and Cheng F*. In silico polypharmacology of natural products. Brief Bioinform, 2018;19(6):1153-1171. (12) Luo YX, Wang XY, Huang YJ, Wang Q*, Fang J*. Systems pharmacology-based investigation of Sanwei Ganjiang Prescription: related mechanisms in liver injury. Chin J Nat Med. 2018;16(10):756-765. (13) Cai C, Fang J*, Guo P, Wang Q, Hong H, Moslehi J, Cheng F*. In Silico Pharmacoepidemiologic Evaluation of Drug-Induced Cardiovascular Complications Using Combined Classifiers. J Chem Inf Model 2018;58(5):943-956 (14) Cai H, Luo Y, Yan X, Fang J*, Wang Q*, Xu J*. The mechanisms of Bushen-Yizhi formula as a therapeutic agent against Alzheimer’s disease. Sci Rep 2018;8(1):3104. (15) Fang J, Gao L, Wang Q*, Cheng F*. Quantitative and systems pharmacology 3. Network-based identification of new targets for natural products enables potential uses in aging-associated disorders. Front Pharmacol. 2017; 8: 747. (16) Fang J#, Wu Z#, Cai C, Wang Q, Tang Y*, Cheng F*. Quantitative and systems pharmacology. 1. In silico prediction of drug-target interactions of natural products enables new targeted cancer therapy. J Chem Inf Model. 2017; 57(11): 2657-2671. (17) Fang J, Wang L, Wu T, Yang C, Gao L, Cai H, Liu J, Fang S, Chen Y, Tan W*, Wang Q*. Network pharmacology-based study on the mechanism of action for herbal medicines in Alzheimer treatment. J Ethnopharmacol. 2017; 196:281-292(18) Fang J, Cai C, Wang Q, Ping L, Zhao Z*, and Cheng F*. Systems Pharmacology-Based Discovery of Natural Products for Precision Oncology Through Targeting Cancer Mutated Genes. CPT Pharmacometrics Syst Pharmacol. 2017; 6(3):177-187.(19) Fang J, Wang L, Li Y, Lian W, Pang X, Wang H, Yuan D, Wang Q, Liu AL*, Du GH*. AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer’s disease. PloS one 12 (5), e0178347. (20) Fang J, Pang X, Yan R, Lian W, Li C, Wang Q, Liu AL*, Du GH*. Discovery of neuroprotective compounds by machine learning approaches. RSC Advances 2016, 6 (12), 9857-9871 (21) Fang J, Pang X, Wu P, Yan R, Gao L, Li C, Lian W, Wang Q, Liu AL*, Du GH*.Molecular Modeling on Berberine Derivatives toward BuChE: An Integrated Study with Quantitative Structure–Activity Relationships Models, Molecular Docking, and Molecular Dynamics Simulations. Chem Biol Drug Des 2016;87(5):649-63. (22) Fang J, Li Y, Liu R, Pang X, Li C, Yang R, He Y, Lian W, Liu AL*, Du GH*. Discovery of multitarget-directed ligands against Alzheimer’s disease through systematic prediction of chemical-protein interactions. J Chem Inf Model. 2015; 55(1): 149-164. (23) Fang J, Yang R, Gao L, Yang S, Pang X, Li C, He Y, Liu AL*, Du GH*. Consensus models for CDK5 inhibitors in silico and their application to inhibitor discovery. Molecular diversity 2014; 19 (1), 149-162. (24) Fang J, Wu P, Yang R, Gao L, Li C, Wang D, Wu S, Liu AL*, Du GH*. Inhibition of acetylcholinesterase by two genistein derivatives: kinetic analysis, molecular docking and molecular dynamics simulation. Acta Pharm Sin B 2014;4(6):430-7.(25) Fang J, Yang R, Gao L, Zhou D, Yang S, Liu AL*, Du GH*. Predictions of BuChE inhibitors using support vector machine and naive Bayesian classification techniques in drug discovery. J Chem Inf Model. 2013;53(11):3009-20.(26) Fang J, Huang D, Zhao W, Ge H, Luo HB*, Xu J*. A new protocol for predicting novel GSK-3β ATP competitive inhibitors. J Chem Inf Model. 2011;51(6):1431-8.中国药理学学会网络药理学委员、中国药理学会中药与天然产物专委会青年常务委员、中国民族医药广东省自然医学学会干细胞与中医再生医学委员会常务委员、广东省药理学会神经与精神药理委员会委员。Pharmacological Research, Journal of Ethnopharmacology, Journal of Functional Foods, Journal of Alzheimer's Disease等20余个SCI期刊审稿专家。 相关热点
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