Researchers develop a molecular docking based webserver to predict drug targets

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.

Journal reference:

Shi, Y., et al. (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.


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