Computational modeling identifies drug candidates for SARS-CoV-2
Scientists from the Division of the National Toxicology Program and their collaborators used computational modeling to probe databases and identify existing drugs that could be repurposed to fight SARS-CoV-2, the virus that causes COVID-19.
Proteases are enzymes that break down proteins. An essential step in the formation of infectious viral particles is the breakdown of precursor viral proteins by viral proteases. Protease inhibitors, a class of antiviral drugs, block the activity of viral proteases. The main protease (Mpro) of SARS-CoV-2 is a proposed target for COVID-19 drugs. The structure and activity of Mpro is highly conserved across the coronavirus family. In this study, previous data on drug interactions with SARS-CoV Mpro was used to develop quantitative structure-activity relationship (QSAR) models, which the team used to virtually screen all drugs in the DrugBank database. They identified 42 drugs that could be repurposed against SARS-CoV-2 Mpro.
Following this discovery, the National Center for Advancing Translational Science (NCATS) released experimental data on the activity of approved clinical drugs against SARS-CoV-2 Mpro. NCATS tested 11 of the 42 drugs identified computationally and 3 showed activity against SARS-CoV-2 Mpro. The work verified the QSAR models’ ability to identify drugs active against SARS-CoV-2. (VP)
Citation: Alves VM, Bobrowski T, Melo-Filho CC, Korn D, Auerbach S, Schmitt C, Muratov EN, Tropsha A. 2020. QSAR modeling of SARS-CoV Mpro inhibitors identifies sufugolix, cenicriviroc, proglumetacin, and other drugs as candidates for repurposing against SARS-CoV-2. Mol Inform; doi:10.1002/minf.202000113 [Online 28 July 2020].