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Computational Identification of Possible Allosteric Sites and Modulators of the SARS-CoV-2 Main Protease.
DasGupta, Debarati; Chan, Wallace K B; Carlson, Heather A.
  • DasGupta D; Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1065, United States.
  • Chan WKB; Department of Pharmacology, University of Michigan, Ann Arbor, Michigan 48109-5632, United States.
  • Carlson HA; Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1065, United States.
J Chem Inf Model ; 62(3): 618-626, 2022 02 14.
Article in English | MEDLINE | ID: covidwho-1671473
ABSTRACT
In this study, we target the main protease (Mpro) of the SARS-CoV-2 virus as it is a crucial enzyme for viral replication. Herein, we report three plausible allosteric sites on Mpro that can expand structure-based drug discovery efforts for new Mpro inhibitors. To find these sites, we used mixed-solvent molecular dynamics (MixMD) simulations, an efficient computational protocol that finds binding hotspots through mapping the surface of unbound proteins with 5% cosolvents in water. We have used normal mode analysis to support our claim of allosteric control for these sites. Further, we have performed virtual screening against the sites with 361 hits from Mpro screenings available through the National Center for Advancing Translational Sciences (NCATS). We have identified the NCATS inhibitors that bind to the remote sites better than the active site of Mpro, and we propose these molecules may be allosteric regulators of the system. After identifying our sites, new X-ray crystal structures were released that show fragment molecules in the sites we found, supporting the notion that these sites are accurate and druggable.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2022 Document Type: Article Affiliation country: Acs.jcim.1c01223

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Limits: Humans Language: English Journal: J Chem Inf Model Journal subject: Medical Informatics / Chemistry Year: 2022 Document Type: Article Affiliation country: Acs.jcim.1c01223