Cargando…

Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significantly impacting human lives, overburdening the healthcare system and weakening global economies. Plant-derived natural compounds are being largely tested for their effic...

Descripción completa

Detalles Bibliográficos
Autores principales: Patel, Chirag N., Jani, Siddhi P., Prasanth Kumar, Sivakumar, Modi, Krunal M., Kumar, Yogesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673090/
https://www.ncbi.nlm.nih.gov/pubmed/36423529
http://dx.doi.org/10.1016/j.compbiomed.2022.106318
_version_ 1784832875890212864
author Patel, Chirag N.
Jani, Siddhi P.
Prasanth Kumar, Sivakumar
Modi, Krunal M.
Kumar, Yogesh
author_facet Patel, Chirag N.
Jani, Siddhi P.
Prasanth Kumar, Sivakumar
Modi, Krunal M.
Kumar, Yogesh
author_sort Patel, Chirag N.
collection PubMed
description The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significantly impacting human lives, overburdening the healthcare system and weakening global economies. Plant-derived natural compounds are being largely tested for their efficacy against COVID-19 targets to combat SARS-CoV-2 infection. The SARS-CoV-2 Main protease (M(pro)) is considered an appealing target because of its role in replication in host cells. We curated a set of 7809 natural compounds by combining the collections of five databases viz Dr Duke's Phytochemical and Ethnobotanical database, IMPPAT, PhytoHub, AromaDb and Zinc. We applied a rigorous computational approach to identify lead molecules from our curated compound set using docking, dynamic simulations, the free energy of binding and DFT calculations. Theaflavin and ginkgetin have emerged as better molecules with a similar inhibition profile in both SARS-CoV-2 and Omicron variants.
format Online
Article
Text
id pubmed-9673090
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-96730902022-11-18 Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus Patel, Chirag N. Jani, Siddhi P. Prasanth Kumar, Sivakumar Modi, Krunal M. Kumar, Yogesh Comput Biol Med Article The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significantly impacting human lives, overburdening the healthcare system and weakening global economies. Plant-derived natural compounds are being largely tested for their efficacy against COVID-19 targets to combat SARS-CoV-2 infection. The SARS-CoV-2 Main protease (M(pro)) is considered an appealing target because of its role in replication in host cells. We curated a set of 7809 natural compounds by combining the collections of five databases viz Dr Duke's Phytochemical and Ethnobotanical database, IMPPAT, PhytoHub, AromaDb and Zinc. We applied a rigorous computational approach to identify lead molecules from our curated compound set using docking, dynamic simulations, the free energy of binding and DFT calculations. Theaflavin and ginkgetin have emerged as better molecules with a similar inhibition profile in both SARS-CoV-2 and Omicron variants. Elsevier Ltd. 2022-12 2022-11-18 /pmc/articles/PMC9673090/ /pubmed/36423529 http://dx.doi.org/10.1016/j.compbiomed.2022.106318 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Patel, Chirag N.
Jani, Siddhi P.
Prasanth Kumar, Sivakumar
Modi, Krunal M.
Kumar, Yogesh
Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus
title Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus
title_full Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus
title_fullStr Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus
title_full_unstemmed Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus
title_short Computational investigation of natural compounds as potential main protease (M(pro)) inhibitors for SARS-CoV-2 virus
title_sort computational investigation of natural compounds as potential main protease (m(pro)) inhibitors for sars-cov-2 virus
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673090/
https://www.ncbi.nlm.nih.gov/pubmed/36423529
http://dx.doi.org/10.1016/j.compbiomed.2022.106318
work_keys_str_mv AT patelchiragn computationalinvestigationofnaturalcompoundsaspotentialmainproteasemproinhibitorsforsarscov2virus
AT janisiddhip computationalinvestigationofnaturalcompoundsaspotentialmainproteasemproinhibitorsforsarscov2virus
AT prasanthkumarsivakumar computationalinvestigationofnaturalcompoundsaspotentialmainproteasemproinhibitorsforsarscov2virus
AT modikrunalm computationalinvestigationofnaturalcompoundsaspotentialmainproteasemproinhibitorsforsarscov2virus
AT kumaryogesh computationalinvestigationofnaturalcompoundsaspotentialmainproteasemproinhibitorsforsarscov2virus