Ontology highlight
ABSTRACT: Motivation
The coronavirus disease 2019 (COVID-19) caused by a new type of coronavirus has been emerging from China and led to thousands of death globally since December 2019. Despite many groups have engaged in studying the newly emerged virus and searching for the treatment of COVID-19, the understanding of the COVID-19 target-ligand interactions represents a key challenge. Herein, we introduce COVID-19 Docking Server, a web server that predicts the binding modes between COVID-19 targets and the ligands including small molecules, peptides and antibodies.Results
Structures of proteins involved in the virus life cycle were collected or constructed based on the homologs of coronavirus, and prepared ready for docking. The meta-platform provides a free and interactive tool for the prediction of COVID-19 target-ligand interactions and following drug discovery for COVID-19.Availability and implementation
http://ncov.schanglab.org.cn.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Kong R
PROVIDER: S-EPMC7558834 | biostudies-literature | 2020 Dec
REPOSITORIES: biostudies-literature
Kong Ren R Yang Guangbo G Xue Rui R Liu Ming M Wang Feng F Hu Jianping J Guo Xiaoqiang X Chang Shan S
Bioinformatics (Oxford, England) 20201201 20
<h4>Motivation</h4>The coronavirus disease 2019 (COVID-19) caused by a new type of coronavirus has been emerging from China and led to thousands of death globally since December 2019. Despite many groups have engaged in studying the newly emerged virus and searching for the treatment of COVID-19, the understanding of the COVID-19 target-ligand interactions represents a key challenge. Herein, we introduce COVID-19 Docking Server, a web server that predicts the binding modes between COVID-19 targe ...[more]