News Release

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

Peer-Reviewed Publication

Compuscript Ltd

D3Targets-2019-nCoV is a webserver built for the purpose to find effective medicines against the SARS-CoV-2

image: D3Targets-2019-nCoV is a webserver built for the purpose to find effective medicines against the SARS-CoV-2 to cure COVID-19, with two functions, one is for predicting target proteins for drugs or active compounds, and the other is for identifying lead compounds against potential drug targets via docking. view more 

Credit: Acta Pharmaceutica Sinica B

A highly effective drug therapy is urgently required to combat coronavirus disease 2019 (COVID-19). The authors of this article have 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 several unique features:

1. Potential target proteins and their different conformations involved in the whole process from virus infection to replication and release are included.
2. All potential ligand-binding sites with a volume larger than 200 Å3 on a protein structure were identified for docking.
3. Correlation information among some conformations or binding sites are annotated.
4. The server is easily updatable, and publicly available.

Currently, the webserver contains 46 proteins [22 severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) encoded proteins and 24 human proteins involved in virus infection, replication and release] with 86 different conformations/structures and 797 potential ligand-binding pockets in total. In this article the authors demonstrate that the webserver should be useful to medicinal chemists, pharmacologists and clinicians for efficiently discovering or developing effective drugs against SARS-CoV-2 to combat COVID-19.

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Article reference: Yulong Shi, Xinben Zhang, Kaijie Mu, Cheng Peng, Zhengdan Zhu, Xiaoyu Wang, Yanqing Yang, Zhijian Xu, Weiliang Zhu, 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, 2020, ISSN 2211-3835, https://doi.org/10.1016/j.apsb.2020.04.006

Keywords: COVID-19, SARS-CoV-2, Target prediction, Multi-conformation, Multi-site Docking, D3Targets-2019-nCoV

The Journal of the Institute of Materia Medica, the Chinese Academy of Medical Sciences and the Chinese Pharmaceutical Association.

Acta Pharmaceutica Sinica B (APSB) is a monthly journal, in English, which publishes significant original research articles, rapid communications and high quality reviews of recent advances in all areas of pharmaceutical sciences -- including pharmacology, pharmaceutics, medicinal chemistry, natural products, pharmacognosy, pharmaceutical analysis and pharmacokinetics.

For more information please visit https://www.journals.elsevier.com/acta-pharmaceutica-sinica-b/

Editorial Board: https://www.journals.elsevier.com/acta-pharmaceutica-sinica-b/editorial-board

APSB is available on ScienceDirect (https://www.sciencedirect.com/journal/acta-pharmaceutica-sinica-b).

Submissions to APSB may be made using Editorial Manager® (https://www.editorialmanager.com/apsb/default.aspx).

CiteScore: 10.5
Impact Factor: 7.097
5-Year Impact Factor: 7.865
Source Normalized Impact per Paper (SNIP): 2.210
SCImago Journal Rank (SJR): 1.792

ISSN 2211-3835


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