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In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs. | LitMetric

In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs.

Sci Rep

Department of Pharmacology, University of Michigan, 2301 MSRBIII, 1150 W Medical Center Dr, Ann Arbor, MI, 48190-5606, USA.

Published: March 2022

AI Article Synopsis

Article Abstract

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires treatments with rapid clinical translatability. Here we develop a multi-target and multi-ligand virtual screening method to identify FDA-approved drugs with potential activity against SARS-CoV-2 at traditional and understudied viral targets. 1,268 FDA-approved small molecule drugs were docked to 47 putative binding sites across 23 SARS-CoV-2 proteins. We compared drugs between binding sites and filtered out compounds that had no reported activity in an in vitro screen against SARS-CoV-2 infection of human liver (Huh-7) cells. This identified 17 "high-confidence", and 97 "medium-confidence" drug-site pairs. The "high-confidence" group was subjected to molecular dynamics simulations to yield six compounds with stable binding poses at their optimal target proteins. Three drugs-amprenavir, levomefolic acid, and calcipotriol-were predicted to bind to 3 different sites on the spike protein, domperidone to the Mac1 domain of the non-structural protein (Nsp) 3, avanafil to Nsp15, and nintedanib to the nucleocapsid protein involved in packaging the viral RNA. Our "two-way" virtual docking screen also provides a framework to prioritize drugs for testing in future emergencies requiring rapidly available clinical drugs and/or treating diseases where a moderate number of targets are known.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963407PMC
http://dx.doi.org/10.1038/s41598-022-08320-yDOI Listing

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