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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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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. |
format | Online Article Text |
id | pubmed-8627846 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
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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