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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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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] |
format | Online Article Text |
id | pubmed-8039805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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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