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Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations
Novel SARS-CoV-2, an etiological factor of Coronavirus disease 2019 (COVID-19), poses a great challenge to the public health care system. Among other druggable targets of SARS-Cov-2, the main protease (M(pro)) is regarded as a prominent enzyme target for drug developments owing to its crucial role i...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514552/ https://www.ncbi.nlm.nih.gov/pubmed/34645849 http://dx.doi.org/10.1038/s41598-021-99165-4 |
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author | Patel, Chirag N. Jani, Siddhi P. Jaiswal, Dharmesh G. Kumar, Sivakumar Prasanth Mangukia, Naman Parmar, Robin M. Rawal, Rakesh M. Pandya, Himanshu A. |
author_facet | Patel, Chirag N. Jani, Siddhi P. Jaiswal, Dharmesh G. Kumar, Sivakumar Prasanth Mangukia, Naman Parmar, Robin M. Rawal, Rakesh M. Pandya, Himanshu A. |
author_sort | Patel, Chirag N. |
collection | PubMed |
description | Novel SARS-CoV-2, an etiological factor of Coronavirus disease 2019 (COVID-19), poses a great challenge to the public health care system. Among other druggable targets of SARS-Cov-2, the main protease (M(pro)) is regarded as a prominent enzyme target for drug developments owing to its crucial role in virus replication and transcription. We pursued a computational investigation to identify M(pro) inhibitors from a compiled library of natural compounds with proven antiviral activities using a hierarchical workflow of molecular docking, ADMET assessment, dynamic simulations and binding free-energy calculations. Five natural compounds, Withanosides V and VI, Racemosides A and B, and Shatavarin IX, obtained better binding affinity and attained stable interactions with M(pro) key pocket residues. These intermolecular key interactions were also retained profoundly in the simulation trajectory of 100 ns time scale indicating tight receptor binding. Free energy calculations prioritized Withanosides V and VI as the top candidates that can act as effective SARS-CoV-2 M(pro) inhibitors. |
format | Online Article Text |
id | pubmed-8514552 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85145522021-10-14 Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations Patel, Chirag N. Jani, Siddhi P. Jaiswal, Dharmesh G. Kumar, Sivakumar Prasanth Mangukia, Naman Parmar, Robin M. Rawal, Rakesh M. Pandya, Himanshu A. Sci Rep Article Novel SARS-CoV-2, an etiological factor of Coronavirus disease 2019 (COVID-19), poses a great challenge to the public health care system. Among other druggable targets of SARS-Cov-2, the main protease (M(pro)) is regarded as a prominent enzyme target for drug developments owing to its crucial role in virus replication and transcription. We pursued a computational investigation to identify M(pro) inhibitors from a compiled library of natural compounds with proven antiviral activities using a hierarchical workflow of molecular docking, ADMET assessment, dynamic simulations and binding free-energy calculations. Five natural compounds, Withanosides V and VI, Racemosides A and B, and Shatavarin IX, obtained better binding affinity and attained stable interactions with M(pro) key pocket residues. These intermolecular key interactions were also retained profoundly in the simulation trajectory of 100 ns time scale indicating tight receptor binding. Free energy calculations prioritized Withanosides V and VI as the top candidates that can act as effective SARS-CoV-2 M(pro) inhibitors. Nature Publishing Group UK 2021-10-13 /pmc/articles/PMC8514552/ /pubmed/34645849 http://dx.doi.org/10.1038/s41598-021-99165-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Article Patel, Chirag N. Jani, Siddhi P. Jaiswal, Dharmesh G. Kumar, Sivakumar Prasanth Mangukia, Naman Parmar, Robin M. Rawal, Rakesh M. Pandya, Himanshu A. Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations |
title | Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations |
title_full | Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations |
title_fullStr | Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations |
title_full_unstemmed | Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations |
title_short | Identification of antiviral phytochemicals as a potential SARS-CoV-2 main protease (M(pro)) inhibitor using docking and molecular dynamics simulations |
title_sort | identification of antiviral phytochemicals as a potential sars-cov-2 main protease (m(pro)) inhibitor using docking and molecular dynamics simulations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514552/ https://www.ncbi.nlm.nih.gov/pubmed/34645849 http://dx.doi.org/10.1038/s41598-021-99165-4 |
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