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Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock

Recent outbreak of COVID-19 caused by SARS-CoV-2 in December 2019 raised global health concerns. Re-purposing the available protease inhibitor drugs for immediate use in treatment in SARS-CoV-2 infections could improve the currently available clinical management. The current study, aims to predict t...

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Detalles Bibliográficos
Autores principales: Mothay, Dipti, Ramesh, K. V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7195910/
https://www.ncbi.nlm.nih.gov/pubmed/32363219
http://dx.doi.org/10.1007/s13337-020-00585-z
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author Mothay, Dipti
Ramesh, K. V.
author_facet Mothay, Dipti
Ramesh, K. V.
author_sort Mothay, Dipti
collection PubMed
description Recent outbreak of COVID-19 caused by SARS-CoV-2 in December 2019 raised global health concerns. Re-purposing the available protease inhibitor drugs for immediate use in treatment in SARS-CoV-2 infections could improve the currently available clinical management. The current study, aims to predict theoretical structure for protease of COVID-19 and to explore further whether this protein can serve as a target for protease inhibitor drugs such as remdesivir, nelfinavir, lopinavir, ritonavir and α-ketoamide. While the 3D structure of protease was predicted using SWISS MODEL server, molecular interaction studies between protein and ligands were performed using AutoDock software. The predicted protease model was reasonably good based on reports generated by different validation servers. The study further revealed that all the protease inhibitor drugs got docked with negative dock energy onto the target protein. Molecular interaction studies showed that protease structure had multiple active site residues for remdesivir, while for remaining ligands the structure had only one active site residue each. From the output of multiple sequence alignment, it is evident that ligand binding sites were conserved. The current in silico study thus, provides structural insights about the protease of COVID-19 and also its molecular interactions with some of the known protease inhibitors. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13337-020-00585-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-71959102020-05-02 Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock Mothay, Dipti Ramesh, K. V. Virusdisease Short Communication Recent outbreak of COVID-19 caused by SARS-CoV-2 in December 2019 raised global health concerns. Re-purposing the available protease inhibitor drugs for immediate use in treatment in SARS-CoV-2 infections could improve the currently available clinical management. The current study, aims to predict theoretical structure for protease of COVID-19 and to explore further whether this protein can serve as a target for protease inhibitor drugs such as remdesivir, nelfinavir, lopinavir, ritonavir and α-ketoamide. While the 3D structure of protease was predicted using SWISS MODEL server, molecular interaction studies between protein and ligands were performed using AutoDock software. The predicted protease model was reasonably good based on reports generated by different validation servers. The study further revealed that all the protease inhibitor drugs got docked with negative dock energy onto the target protein. Molecular interaction studies showed that protease structure had multiple active site residues for remdesivir, while for remaining ligands the structure had only one active site residue each. From the output of multiple sequence alignment, it is evident that ligand binding sites were conserved. The current in silico study thus, provides structural insights about the protease of COVID-19 and also its molecular interactions with some of the known protease inhibitors. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13337-020-00585-z) contains supplementary material, which is available to authorized users. Springer India 2020-05-02 2020-06 /pmc/articles/PMC7195910/ /pubmed/32363219 http://dx.doi.org/10.1007/s13337-020-00585-z Text en © Indian Virological Society 2020
spellingShingle Short Communication
Mothay, Dipti
Ramesh, K. V.
Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
title Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
title_full Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
title_fullStr Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
title_full_unstemmed Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
title_short Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
title_sort binding site analysis of potential protease inhibitors of covid-19 using autodock
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7195910/
https://www.ncbi.nlm.nih.gov/pubmed/32363219
http://dx.doi.org/10.1007/s13337-020-00585-z
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