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Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease
In recent times, the emergence of novel Coronavirus and the successive mutations in the viral genome has posed a major threat to public health with strikingly high mortality and morbidity rates across the globe. To address the health concern, the current scenario demands the need for effective thera...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184101/ http://dx.doi.org/10.1007/s40995-023-01474-y |
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author | Joel, C. Jebakumar, D. S. Ivan Bennie, R. Biju Ebenezer, Cheriyan Solomon, Rajadurai Vijay Abraham, S. Daniel |
author_facet | Joel, C. Jebakumar, D. S. Ivan Bennie, R. Biju Ebenezer, Cheriyan Solomon, Rajadurai Vijay Abraham, S. Daniel |
author_sort | Joel, C. |
collection | PubMed |
description | In recent times, the emergence of novel Coronavirus and the successive mutations in the viral genome has posed a major threat to public health with strikingly high mortality and morbidity rates across the globe. To address the health concern, the current scenario demands the need for effective therapeutics and at present, the anti-viral drug Remdesivir has been used worldwide to combat the disease. Therefore, in this present study, we have adopted structure-based virtual screening approach to assess the inhibitory potential of the five structural analogues of Remdesivir (Rm) against SARS-CoV-2 main protease (M(pro)) using Autodock molecular docking tool. Density functional theory (DFT) calculations have been carried out to gain deep insights into the electronic structure of these analogues. The low HOMO–LUMO gap implies that Rm3 is chemically active and MEP analysis shed light on the possible regions of electronic charge distribution. From the docking results, the analogue compound Rm5 has been identified to exhibit effective inhibitory effect with higher binding affinity (−7.8 kcal mol(−1)). Most of the docked compounds, however, were found to exhibit good drug-likeness properties and hence could serve as potential candidates against SARS-CoV-2 Corona virus. |
format | Online Article Text |
id | pubmed-10184101 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-101841012023-05-16 Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease Joel, C. Jebakumar, D. S. Ivan Bennie, R. Biju Ebenezer, Cheriyan Solomon, Rajadurai Vijay Abraham, S. Daniel Iran J Sci Research Paper In recent times, the emergence of novel Coronavirus and the successive mutations in the viral genome has posed a major threat to public health with strikingly high mortality and morbidity rates across the globe. To address the health concern, the current scenario demands the need for effective therapeutics and at present, the anti-viral drug Remdesivir has been used worldwide to combat the disease. Therefore, in this present study, we have adopted structure-based virtual screening approach to assess the inhibitory potential of the five structural analogues of Remdesivir (Rm) against SARS-CoV-2 main protease (M(pro)) using Autodock molecular docking tool. Density functional theory (DFT) calculations have been carried out to gain deep insights into the electronic structure of these analogues. The low HOMO–LUMO gap implies that Rm3 is chemically active and MEP analysis shed light on the possible regions of electronic charge distribution. From the docking results, the analogue compound Rm5 has been identified to exhibit effective inhibitory effect with higher binding affinity (−7.8 kcal mol(−1)). Most of the docked compounds, however, were found to exhibit good drug-likeness properties and hence could serve as potential candidates against SARS-CoV-2 Corona virus. Springer International Publishing 2023-05-15 2023 /pmc/articles/PMC10184101/ http://dx.doi.org/10.1007/s40995-023-01474-y Text en © The Author(s), under exclusive licence to Shiraz University 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Research Paper Joel, C. Jebakumar, D. S. Ivan Bennie, R. Biju Ebenezer, Cheriyan Solomon, Rajadurai Vijay Abraham, S. Daniel Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease |
title | Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease |
title_full | Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease |
title_fullStr | Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease |
title_full_unstemmed | Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease |
title_short | Computational Insights and Virtual Screening of Repurposed FDA-Approved Drug Against SARS-CoV-2 Protease |
title_sort | computational insights and virtual screening of repurposed fda-approved drug against sars-cov-2 protease |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184101/ http://dx.doi.org/10.1007/s40995-023-01474-y |
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