| Literature DB >> 32745502 |
Liqian Zhou1, Juanjuan Wang1, Guangyi Liu1, Qingqing Lu2, Ruyi Dong2, Geng Tian2, Jialiang Yang3, Lihong Peng4.
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.Entities:
Keywords: Antiviral drug; Molecular docking; SARS-CoV-2; VDA; VDA-KATZ
Year: 2020 PMID: 32745502 DOI: 10.1016/j.ygeno.2020.07.044
Source DB: PubMed Journal: Genomics ISSN: 0888-7543 Impact factor: 5.736