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High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor
Author(s) -
Austin Clyde,
Stephanie Galanie,
Daniel W. Kneller,
Heng Ma,
Yadu Babuji,
Ben Blaiszik,
Alexander Brace,
Thomas Brettin,
Kyle Chard,
Ryan Chard,
Leighton Coates,
Ian Foster,
Darin Hauner,
Vilmos Kertész,
Neeraj Kumar,
Hyungro Lee,
Zhuozhao Li,
André Merzky,
Jürgen Schmidt,
Li Lynn Tan,
Mikhail Titov,
Anda Trifan,
Matteo Turilli,
Hubertus J. J. van Dam,
Srinivas C. Chennubhotla,
Shantenu Jha,
Andrey Kovalevsky,
Arvind Ramanathan,
Martha S. Head,
Rick Stevens
Publication year - 2021
Publication title -
journal of chemical information and modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 160
eISSN - 1549-960X
pISSN - 1549-9596
DOI - 10.1021/acs.jcim.1c00851
Subject(s) - virtual screening , protease , computational biology , docking (animal) , context (archaeology) , small molecule , covid-19 , protein–protein interaction , chemistry , hydrophobic effect , hydrogen bond , binding site , drug discovery , molecule , biology , enzyme , biochemistry , medicine , paleontology , nursing , disease , organic chemistry , pathology , infectious disease (medical specialty)
Despite the recent availability of vaccines against the acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the search for inhibitory therapeutic agents has assumed importance especially in the context of emerging new viral variants. In this paper, we describe the discovery of a novel noncovalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits the SARS-Cov-2 main protease (M pro ) by employing a scalable high-throughput virtual screening (HTVS) framework and a targeted compound library of over 6.5 million molecules that could be readily ordered and purchased. Our HTVS framework leverages the U.S. supercomputing infrastructure achieving nearly 91% resource utilization and nearly 126 million docking calculations per hour. Downstream biochemical assays validate this M pro inhibitor with an inhibition constant ( K i ) of 2.9 μM (95% CI 2.2, 4.0). Furthermore, using room-temperature X-ray crystallography, we show that MCULE-5948770040 binds to a cleft in the primary binding site of M pro forming stable hydrogen bond and hydrophobic interactions. We then used multiple μs-time scale molecular dynamics (MD) simulations and machine learning (ML) techniques to elucidate how the bound ligand alters the conformational states accessed by M pro , involving motions both proximal and distal to the binding site. Together, our results demonstrate how MCULE-5948770040 inhibits M pro and offers a springboard for further therapeutic design.

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