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Briefings in bioinformatics. 2021 Mar 22;22(2):946-962. doi: 10.1093/bib/bbaa260 Q16.82024

MCCS: a novel recognition pattern-based method for fast track discovery of anti-SARS-CoV-2 drugs

MCCS:一种基于新型识别模式的快速发现抗SARS-CoV-2药物的方法 翻译改进

Zhiwei Feng  1, Maozi Chen  1, Ying Xue  1, Tianjian Liang  1, Hui Chen  1, Yuehan Zhou  1, Thomas D Nolin  1, Randall B Smith  1, Xiang-Qun Xie  1

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  • 1 University of Pittsburgh.
  • DOI: 10.1093/bib/bbaa260 PMID: 33078827

    摘要 Ai翻译

    Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, or 2019-nCoV), there is an urgent need to identify therapeutics that are effective against COVID-19 before vaccines are available. Since the current rate of SARS-CoV-2 knowledge acquisition via traditional research methods is not sufficient to match the rapid spread of the virus, novel strategies of drug discovery for SARS-CoV-2 infection are required. Structure-based virtual screening for example relies primarily on docking scores and does not take the importance of key residues into consideration, which may lead to a significantly higher incidence rate of false-positive results. Our novel in silico approach, which overcomes these limitations, can be utilized to quickly evaluate FDA-approved drugs for repurposing and combination, as well as designing new chemical agents with therapeutic potential for COVID-19. As a result, anti-HIV or antiviral drugs (lopinavir, tenofovir disoproxil, fosamprenavir and ganciclovir), antiflu drugs (peramivir and zanamivir) and an anti-HCV drug (sofosbuvir) are predicted to bind to 3CLPro in SARS-CoV-2 with therapeutic potential for COVID-19 infection by our new protocol. In addition, we also propose three antidiabetic drugs (acarbose, glyburide and tolazamide) for the potential treatment of COVID-19. Finally, we apply our new virus chemogenomics knowledgebase platform with the integrated machine-learning computing algorithms to identify the potential drug combinations (e.g. remdesivir+chloroquine), which are congruent with ongoing clinical trials. In addition, another 10 compounds from CAS COVID-19 antiviral candidate compounds dataset are also suggested by Molecular Complex Characterizing System with potential treatment for COVID-19. Our work provides a novel strategy for the repurposing and combinations of drugs in the market and for prediction of chemical candidates with anti-COVID-19 potential.

    Keywords: COVID-19; MCCS; drug combination; drug repurposing; residue energy contribution.

    Keywords:anti-SARS-CoV-2 drugs

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    期刊名:Briefings in bioinformatics

    缩写:BRIEF BIOINFORM

    ISSN:1467-5463

    e-ISSN:1477-4054

    IF/分区:6.8/Q1

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