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Probing antiviral drugs against SARS-CoV-2 through virus-drug association prediction based on the KATZ method.

Authors :
Zhou L
Wang J
Liu G
Lu Q
Dong R
Tian G
Yang J
Peng L
Source :
Genomics [Genomics] 2020 Nov; Vol. 112 (6), pp. 4427-4434. Date of Electronic Publication: 2020 Jul 31.
Publication Year :
2020

Abstract

It is urgent to find an effective antiviral drug against SARS-CoV-2. In this study, 96 virus-drug associations (VDAs) from 12 viruses including SARS-CoV-2 and similar viruses and 78 small molecules are selected. Complete genomic sequence similarity of viruses and chemical structure similarity of drugs are then computed. A KATZ-based VDA prediction method (VDA-KATZ) is developed to infer possible drugs associated with SARS-CoV-2. VDA-KATZ obtained the best AUCs of 0.8803 when the walking length is 2. The predicted top 3 antiviral drugs against SARS-CoV-2 are remdesivir, oseltamivir, and zanamivir. Molecular docking is conducted between the predicted top 10 drugs and the virus spike protein/human ACE2. The results showed that the above 3 chemical agents have higher molecular binding energies with ACE2. For the first time, we found that zidovudine may be effective clues of treatment of COVID-19. We hope that our predicted drugs could help to prevent the spreading of COVID.<br /> (Copyright © 2020. Published by Elsevier Inc.)

Details

Language :
English
ISSN :
1089-8646
Volume :
112
Issue :
6
Database :
MEDLINE
Journal :
Genomics
Publication Type :
Academic Journal
Accession number :
32745502
Full Text :
https://doi.org/10.1016/j.ygeno.2020.07.044