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Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening.

ABSTRACT: Background: Conserved domains within SARS-CoV-2 nonstructural proteins represent key targets for the design of novel inhibitors. Methods: The authors aimed to identify potential SARS-CoV-2 NSP5 inhibitors using the ZINC database along with structure-based virtual screening and molecular dynamics simulation. Results: Of 13,840 compounds, 353 with robust docking scores were initially chosen, of which ten hit compounds were selected as candidates for detailed analyses. Three compounds were selected as coronavirus NSP5 inhibitors after passing absorption, distribution, metabolism, excretion and toxicity study; root and mean square deviation; and radius of gyration calculations. Conclusion: ZINC000049899562, ZINC000169336666 and ZINC000095542577 are potential NSP5 protease inhibitors that warrant further experimental studies.

SUBMITTER: Hakami AR

PROVIDER: S-EPMC8612299 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening.

Hakami Abdulrahim R AR Bakheit Ahmed H AH Almehizia Abdulrahman A AA Ghazwani Mohammed Y MY

Future medicinal chemistry 20211124 2

Background: Conserved domains within SARS-CoV-2 nonstructural proteins represent key targets for the design of novel inhibitors. Methods: The authors aimed to identify potential SARS-CoV-2 NSP5 inhibitors using the ZINC database along with structure-based virtual screening and molecular dynamics simulation. Results: Of 13,840 compounds, 353 with robust docking scores were initially chosen, of which ten hit compounds were selected as candidates for detailed analyses. Three co ...[more]

PMID: 34814706

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Project description:The COVID-19 disease is caused by a new strain of the coronavirus family (SARS-CoV-2), and it has affected at present millions of people all over the world. The indispensable role of the main protease (Mpro) in viral replication and gene expression makes this enzyme an attractive drug target. Therefore, inhibition of SARS-CoV-2 Mpro as a proposition to halt virus ingression is being pursued by scientists globally. Here we carried out a study with two objectives: the first being to perform comparative protein sequence and 3D structural analysis to understand the effect of 12 point mutations on the active site. Among these, two mutations, viz., Ser46 and Phe134, were found to cause a significant change at the active sites of SARS-CoV-2. The Ser46 mutation present at the entrance of the S5 subpocket of SARS-CoV-2 increases the contribution of other two hydrophilic residues, while the Phe134 mutation, present in the catalytic cysteine loop, can cause an increase in catalytic efficiency of Mpro by facilitating fast proton transfer from the Cys145 to His41 residue. It was observed that active site remained conserved among Mpro of both SARS-CoVs, except at the entrance of the S5 subpocket, suggesting sustenance of substrate specificity. The second objective was to screen the inhibitory effects of three different data sets (natural products, coronaviruses main protease inhibitors, and FDA-approved drugs) using a structure-based virtual screening approach. A total of 73 hits had a combo score >2.0. Eight different structural scaffold classes were identified, such as one/two tetrahydropyran ring(s), dipeptide/tripeptide/oligopeptide, large (approximately 20 atoms) cyclic peptide, and miscellaneous. The screened hits showed key interactions with subpockets of the active site. Further, molecular dynamics studies of selected screened compounds confirmed their perfect fitting into the subpockets of the active site. This study suggests promising structures that can fit into the SARS-CoV-2 Mpro active site and also offers direction for further lead optimization and rational drug design.

Dataset Information

Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening.

Publications

Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening.

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