Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 60, Issue 10, Pages 5080-5102Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.0c00634
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Funding
- National Institutes of Health Common Fund [U24HG006941]
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A new coronavirus (SARS-CoV-2) is a global threat to world health and economy. Its dimeric main protease (M-pro), which is required for the proteolytic cleavage of viral precursor proteins, is a good candidate for drug development owing to its conservation and the absence of a human homolog. Improving our understanding of M-pro behavior can accelerate the discovery of effective therapies to reduce mortality. All-atom molecular dynamics (MD) simulations (100 ns) of 50 mutant M-pro dimers obtained from filtered sequences from the GISAID database were analyzed using root-mean-square deviation, root-mean-square fluctuation, R-g, averaged betweenness centrality, and geometry calculations. The results showed that SARS-CoV-2 M-pro essentially behaves in a similar manner to its SAR-CoV homolog. However, we report the following new findings from the variants: (1) Residues GLY15, VAL157, and PRO184 have mutated more than once in SARS CoV-2; (2) the D48E variant has lead to a novel TSEEMLN loop at the binding pocket; (3) inactive apo M-pro does not show signs of dissociation in 100 ns MD; (4) a non-canonical pose for PHE140 widens the substrate binding surface; (5) dual allosteric pockets coinciding with various stabilizing and functional components of the substrate binding pocket were found to display correlated compaction dynamics; (6) high betweenness centrality values for residues 17 and 128 in all M-pro samples suggest their high importance in dimer stability-one such consequence has been observed for the M17I mutation whereby one of the N-fingers was highly unstable. (7) Independent coarse-grained Monte Carlo simulations suggest a relationship between the rigidity/mutability and enzymatic function. Our entire approach combining database preparation, variant retrieval, homology modeling, dynamic residue network (DRN), relevant conformation retrieval from 1-D kernel density estimates from reaction coordinates to other existing approaches of structural analysis, and data visualization within the coronaviral M-pro is also novel and is applicable to other coronaviral proteins.
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