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Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences

Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CL(pro) inhibitory property were taken into consideration for building different...

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Autores principales: Adhikari, Nilanjan, Banerjee, Suvankar, Baidya, Sandip Kumar, Ghosh, Balaram, Jha, Tarun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627846/
https://www.ncbi.nlm.nih.gov/pubmed/34866654
http://dx.doi.org/10.1016/j.molstruc.2021.132041
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author Adhikari, Nilanjan
Banerjee, Suvankar
Baidya, Sandip Kumar
Ghosh, Balaram
Jha, Tarun
author_facet Adhikari, Nilanjan
Banerjee, Suvankar
Baidya, Sandip Kumar
Ghosh, Balaram
Jha, Tarun
author_sort Adhikari, Nilanjan
collection PubMed
description Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CL(pro) inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CL(pro) inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CL(pro) inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CL(pro) inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future.
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spelling pubmed-86278462021-11-29 Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences Adhikari, Nilanjan Banerjee, Suvankar Baidya, Sandip Kumar Ghosh, Balaram Jha, Tarun J Mol Struct Article Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CL(pro) inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CL(pro) inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CL(pro) inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CL(pro) inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future. Elsevier B.V. 2022-03-05 2021-11-29 /pmc/articles/PMC8627846/ /pubmed/34866654 http://dx.doi.org/10.1016/j.molstruc.2021.132041 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
Adhikari, Nilanjan
Banerjee, Suvankar
Baidya, Sandip Kumar
Ghosh, Balaram
Jha, Tarun
Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences
title Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences
title_full Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences
title_fullStr Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences
title_full_unstemmed Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences
title_short Ligand-based quantitative structural assessments of SARS-CoV-2 3CL(pro) inhibitors: An analysis in light of structure-based multi-molecular modeling evidences
title_sort ligand-based quantitative structural assessments of sars-cov-2 3cl(pro) inhibitors: an analysis in light of structure-based multi-molecular modeling evidences
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627846/
https://www.ncbi.nlm.nih.gov/pubmed/34866654
http://dx.doi.org/10.1016/j.molstruc.2021.132041
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