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Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations

SARS-CoV-2 has rapidly emerged as a global pandemic with high infection rate. At present, there is no drug available for this deadly disease. Recently, M(pro) (Main Protease) enzyme has been identified as essential proteins for the survival of this virus. In the present work, Lipinski's rules a...

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Autores principales: Masand, Vijay H., Sk, Md Fulbabu, Kar, Parimal, Rastija, Vesna, Zaki, Magdi E.A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295492/
https://www.ncbi.nlm.nih.gov/pubmed/34312571
http://dx.doi.org/10.1016/j.chemolab.2021.104394
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author Masand, Vijay H.
Sk, Md Fulbabu
Kar, Parimal
Rastija, Vesna
Zaki, Magdi E.A.
author_facet Masand, Vijay H.
Sk, Md Fulbabu
Kar, Parimal
Rastija, Vesna
Zaki, Magdi E.A.
author_sort Masand, Vijay H.
collection PubMed
description SARS-CoV-2 has rapidly emerged as a global pandemic with high infection rate. At present, there is no drug available for this deadly disease. Recently, M(pro) (Main Protease) enzyme has been identified as essential proteins for the survival of this virus. In the present work, Lipinski's rules and molecular docking have been performed to identify plausible inhibitors of M(pro) using food compounds. For virtual screening, a database of food compounds was downloaded and then filtered using Lipinski's rule of five. Then, molecular docking was accomplished to identify hits using M(pro) protein as the target enzyme. This led to identification of a Spermidine derivative as a hit. In the next step, Spermidine derivatives were collected from PubMed and screened for their binding with M(pro) protein. In addition, molecular dynamic simulations (200 ns) were executed to get additional information. Some of the compounds are found to have strong affinity for M(pro), therefore these hits could be used to develop a therapeutic agent for SARS-CoV-2.
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spelling pubmed-82954922021-07-22 Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations Masand, Vijay H. Sk, Md Fulbabu Kar, Parimal Rastija, Vesna Zaki, Magdi E.A. Chemometr Intell Lab Syst Article SARS-CoV-2 has rapidly emerged as a global pandemic with high infection rate. At present, there is no drug available for this deadly disease. Recently, M(pro) (Main Protease) enzyme has been identified as essential proteins for the survival of this virus. In the present work, Lipinski's rules and molecular docking have been performed to identify plausible inhibitors of M(pro) using food compounds. For virtual screening, a database of food compounds was downloaded and then filtered using Lipinski's rule of five. Then, molecular docking was accomplished to identify hits using M(pro) protein as the target enzyme. This led to identification of a Spermidine derivative as a hit. In the next step, Spermidine derivatives were collected from PubMed and screened for their binding with M(pro) protein. In addition, molecular dynamic simulations (200 ns) were executed to get additional information. Some of the compounds are found to have strong affinity for M(pro), therefore these hits could be used to develop a therapeutic agent for SARS-CoV-2. Elsevier B.V. 2021-10-15 2021-07-22 /pmc/articles/PMC8295492/ /pubmed/34312571 http://dx.doi.org/10.1016/j.chemolab.2021.104394 Text en © 2021 Elsevier B.V. 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
Masand, Vijay H.
Sk, Md Fulbabu
Kar, Parimal
Rastija, Vesna
Zaki, Magdi E.A.
Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations
title Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations
title_full Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations
title_fullStr Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations
title_full_unstemmed Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations
title_short Identification of Food Compounds as inhibitors of SARS-CoV-2 main protease using molecular docking and molecular dynamics simulations
title_sort identification of food compounds as inhibitors of sars-cov-2 main protease using molecular docking and molecular dynamics simulations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295492/
https://www.ncbi.nlm.nih.gov/pubmed/34312571
http://dx.doi.org/10.1016/j.chemolab.2021.104394
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