Multi-targeting approach for nsp3, nsp9, nsp12 and nsp15 proteins of SARS-CoV-2 by Diosmin as illustrated by molecular docking and molecular dynamics simulation methodologies.
Antiviral Agents
/ pharmacology
COVID-19
/ virology
Coronavirus Papain-Like Proteases
/ antagonists & inhibitors
Coronavirus RNA-Dependent RNA Polymerase
/ antagonists & inhibitors
Diosmin
/ pharmacology
Drug Discovery
Endoribonucleases
/ antagonists & inhibitors
Humans
Ligands
Molecular Docking Simulation
Molecular Dynamics Simulation
RNA-Binding Proteins
SARS-CoV-2
/ metabolism
Viral Nonstructural Proteins
/ antagonists & inhibitors
COVID-19 Drug Treatment
FDA-approved drugs
MD simulation
Molecular docking
Multi-targeting
SARS-CoV-2
Journal
Methods (San Diego, Calif.)
ISSN: 1095-9130
Titre abrégé: Methods
Pays: United States
ID NLM: 9426302
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
received:
03
12
2020
revised:
19
02
2021
accepted:
22
02
2021
pubmed:
28
2
2021
medline:
10
11
2021
entrez:
27
2
2021
Statut:
ppublish
Résumé
Novel coronavirus SARS-CoV-2continues tospread rapidly worldwide and causing serious health and economic loss. In the absence of any effective treatment, various in-silico approaches are being explored towards the therapeutic discovery against COVID-19. Targeting multiple key enzymes of SARS-CoV-2 with a single potential drug could be an important in-silico strategy to tackle the therapeutic emergency. A number of Food and Drug Administration (FDA) approved drugs entered into clinical stages were originated from multi-target approaches with an increased rate, 16-21% between 2015 and 2017. In this study, we selected an FDA-approved library (Prestwick Chemical Library of 1520 compounds) and implemented in-silico virtual screening against multiple protein targets of SARS-CoV-2 on the Glide module of Schrödinger software (release 2020-1). Compounds were analyzed for their docking scores and the top-ranked against each targeted protein were further subjected to Molecular Dynamics (MD) simulations to assess the binding stability of ligand-protein complexes. A multi-targeting approach was optimized that enabled the analysis of several compounds' binding efficiency with more than one protein targets. It was demonstrated that Diosmin (6) showed the highest binding affinity towards multiple targets with binding free energy (kcal/mol) values of -63.39 (nsp3); -62.89 (nsp9); -31.23 (nsp12); and -65.58 (nsp15). Therefore, our results suggests that Diosmin (6) possesses multi-targeting capability, a potent inhibitor of various non-structural proteins of SARS-CoV-2, and thus it deserves further validation experiments before using as a therapeutic against COVID-19 disease.
Identifiants
pubmed: 33639316
pii: S1046-2023(21)00062-1
doi: 10.1016/j.ymeth.2021.02.017
pmc: PMC7904494
pii:
doi:
Substances chimiques
Antiviral Agents
0
Ligands
0
NSP9 protein, SARS-CoV-2
0
RNA-Binding Proteins
0
Viral Nonstructural Proteins
0
Diosmin
7QM776WJ5N
Coronavirus RNA-Dependent RNA Polymerase
EC 2.7.7.48
NSP12 protein, SARS-CoV-2
EC 2.7.7.48
Endoribonucleases
EC 3.1.-
nidoviral uridylate-specific endoribonuclease
EC 3.1.-
Coronavirus Papain-Like Proteases
EC 3.4.22.2
papain-like protease, SARS-CoV-2
EC 3.4.22.2
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
44-56Informations de copyright
Copyright © 2021 Elsevier Inc. All rights reserved.
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