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D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19

文献类型：期刊论文

作者Shi, Yulong1,2; Zhang, Xinben2; Mu, Kaijie2,3; Peng, Cheng1,2; Zhu, Zhengdan1,2; Wang, Xiaoyu2; Yang, Yanqing1,2; Xu, Zhijian1,2; Zhu, Weiliang1,2
刊名ACTA PHARMACEUTICA SINICA B
出版日期2020-07-01
卷号10期号:7页码:1239-1248
关键词COVID-19 SARS-CoV-2 Target prediction Multi-conformation Multi-site Docking D3Targets-2019-nCoV
ISSN号2211-3835
DOI10.1016/j.apsb.2020.04.006
通讯作者Xu, Zhijian(zjxu@simm.ac.cn) ; Zhu, Weiliang(wlzhu@simm.ac.cn)
英文摘要A highly effective medicine is urgently required to cure coronavirus disease 2019 (COVID-19). For the purpose, we developed a molecular docking based webserver, namely D3Targets-2019-nCoV, with two functions, one is for predicting drug targets for drugs or active compounds observed from clinic or in vitro/in vivo studies, the other is for identifying lead compounds against potential drug targets via docking. This server has its unique features, (1) the potential target proteins and their different conformations involving in the whole process from virus infection to replication and release were included as many as possible; (2) all the potential ligand-binding sites with volume larger than 200 angstrom(3) on a protein structure were identified for docking; (3) correlation information among some conformations or binding sites was annotated; (4) it is easy to be updated, and is accessible freely to public (https://www.d3pharma.com/D3Targets-2019-nCoV/index.php). Currently, the webserver contains 42 proteins [20 severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) encoded proteins and 22 human proteins involved in virus infection, replication and release] with 69 different conformations/structures and 557 potential ligand-binding pockets in total. With 6 examples, we demonstrated that the webserver should be useful to medicinal chemists, pharmacologists and clinicians for efficiently discovering or developing effective drugs against the SARS-CoV-2 to cure COVID-19. (C) 2020 Chinese Pharmaceutical Association and Institute of Materia Medica, Chinese Academy of Medical Sciences. Production and hosting by Elsevier B.V.
WOS关键词DOCKING ; VIRUS
资助项目National Key Research and Development Program of China[2017YFB0202601] ; National Key Research and Development Program of China[2016YFA0502301]
WOS研究方向Pharmacology & Pharmacy
语种英语
WOS记录号WOS:000561284200009
出版者INST MATERIA MEDICA, CHINESE ACAD MEDICAL SCIENCES
源URL[http://119.78.100.183/handle/2S10ELR8/292335]  
专题中国科学院上海药物研究所
通讯作者Xu, Zhijian; Zhu, Weiliang
作者单位1.Univ Chinese Acad Sci, Sch Pharm, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, Key Lab Receptor Res, Shanghai 201203, Peoples R China
3.Univ Sci & Technol China, Nano Sci & Technol Inst, Suzhou 215123, Peoples R China
推荐引用方式
GB/T 7714		 Shi, Yulong,Zhang, Xinben,Mu, Kaijie,et al. D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19[J]. ACTA PHARMACEUTICA SINICA B,2020,10(7):1239-1248.
APA Shi, Yulong.,Zhang, Xinben.,Mu, Kaijie.,Peng, Cheng.,Zhu, Zhengdan.,...&Zhu, Weiliang.(2020).D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19.ACTA PHARMACEUTICA SINICA B,10(7),1239-1248.
MLA Shi, Yulong,et al."D3Targets-2019-nCoV: a webserver for predicting drug targets and for multi-target and multi-site based virtual screening against COVID-19".ACTA PHARMACEUTICA SINICA B 10.7(2020):1239-1248.

入库方式： OAI收割

来源：上海药物研究所

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