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Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach

ABSTRACT: Worldwide coronavirus disease 2019 (COVID-19) outbreak is still threatening global health since its outbreak first reported in the late 2019. The causative novel virus has been designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although COVID-19 emergent with signi...

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Autores principales: Bhowmick, Shovonlal, Saha, Achintya, Osman, Sameh Mohamed, Alasmary, Fatmah Ali, Almutairi, Tahani Mazyad, Islam, Md Ataul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8039805/
https://www.ncbi.nlm.nih.gov/pubmed/33844135
http://dx.doi.org/10.1007/s11030-021-10214-6
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author Bhowmick, Shovonlal
Saha, Achintya
Osman, Sameh Mohamed
Alasmary, Fatmah Ali
Almutairi, Tahani Mazyad
Islam, Md Ataul
author_facet Bhowmick, Shovonlal
Saha, Achintya
Osman, Sameh Mohamed
Alasmary, Fatmah Ali
Almutairi, Tahani Mazyad
Islam, Md Ataul
author_sort Bhowmick, Shovonlal
collection PubMed
description ABSTRACT: Worldwide coronavirus disease 2019 (COVID-19) outbreak is still threatening global health since its outbreak first reported in the late 2019. The causative novel virus has been designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although COVID-19 emergent with significant mortality, there is no availability of definite treatment measures. It is now extremely desirable to identify potential chemical entities against SARS-CoV-2 for the treatment of COVID-19. In the present study, a state-of-art virtual screening protocol was implemented on three anti-viral specific chemical libraries against SARS-CoV-2 main protease (M(pro)). Particularly, viewing the large-scale biological role of M(pro) in the viral replication process it has been considered as a prospective anti-viral drug target. Herein, on collected 79,892 compounds, hierarchical multistep docking followed by relative binding free energy estimation has been performed. Thereafter, implying a user-defined XP-dock and MM-GBSA cut-off scores as −8.00 and −45.00 kcal/mol, chemical space has been further reduced. Exhaustive molecular binding interactions analyses and various pharmacokinetics profiles assessment suggested four compounds (ChemDiv_D658-0159, ChemDiv_F431-0433, Enamine_Z3019991843 and Asinex_LAS_51389260) as potent inhibitors/modulators of SARS-CoV-2 M(pro). In-depth protein–ligand interactions stability in the dynamic state has been evaluated by 100 ns molecular dynamics (MD) simulation studies along with MM-GBSA-based binding free energy estimations of entire simulation trajectories that have revealed strong binding affinity of all identified compounds towards M(pro). Hence, all four identified compounds might be considered as promising candidates for future drug development specifically targeting the SARS-CoV-2 M(pro); however, they also need experimental assessment for a better understanding of molecular interaction mechanisms. GRAPHIC ABSTRACT: [Image: see text]
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spelling pubmed-80398052021-04-12 Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach Bhowmick, Shovonlal Saha, Achintya Osman, Sameh Mohamed Alasmary, Fatmah Ali Almutairi, Tahani Mazyad Islam, Md Ataul Mol Divers Original Article ABSTRACT: Worldwide coronavirus disease 2019 (COVID-19) outbreak is still threatening global health since its outbreak first reported in the late 2019. The causative novel virus has been designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although COVID-19 emergent with significant mortality, there is no availability of definite treatment measures. It is now extremely desirable to identify potential chemical entities against SARS-CoV-2 for the treatment of COVID-19. In the present study, a state-of-art virtual screening protocol was implemented on three anti-viral specific chemical libraries against SARS-CoV-2 main protease (M(pro)). Particularly, viewing the large-scale biological role of M(pro) in the viral replication process it has been considered as a prospective anti-viral drug target. Herein, on collected 79,892 compounds, hierarchical multistep docking followed by relative binding free energy estimation has been performed. Thereafter, implying a user-defined XP-dock and MM-GBSA cut-off scores as −8.00 and −45.00 kcal/mol, chemical space has been further reduced. Exhaustive molecular binding interactions analyses and various pharmacokinetics profiles assessment suggested four compounds (ChemDiv_D658-0159, ChemDiv_F431-0433, Enamine_Z3019991843 and Asinex_LAS_51389260) as potent inhibitors/modulators of SARS-CoV-2 M(pro). In-depth protein–ligand interactions stability in the dynamic state has been evaluated by 100 ns molecular dynamics (MD) simulation studies along with MM-GBSA-based binding free energy estimations of entire simulation trajectories that have revealed strong binding affinity of all identified compounds towards M(pro). Hence, all four identified compounds might be considered as promising candidates for future drug development specifically targeting the SARS-CoV-2 M(pro); however, they also need experimental assessment for a better understanding of molecular interaction mechanisms. GRAPHIC ABSTRACT: [Image: see text] Springer International Publishing 2021-04-12 2021 /pmc/articles/PMC8039805/ /pubmed/33844135 http://dx.doi.org/10.1007/s11030-021-10214-6 Text en © Crown 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Bhowmick, Shovonlal
Saha, Achintya
Osman, Sameh Mohamed
Alasmary, Fatmah Ali
Almutairi, Tahani Mazyad
Islam, Md Ataul
Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
title Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
title_full Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
title_fullStr Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
title_full_unstemmed Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
title_short Structure-based identification of SARS-CoV-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
title_sort structure-based identification of sars-cov-2 main protease inhibitors from anti-viral specific chemical libraries: an exhaustive computational screening approach
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8039805/
https://www.ncbi.nlm.nih.gov/pubmed/33844135
http://dx.doi.org/10.1007/s11030-021-10214-6
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