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

Abstract 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...
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Autor*in:	Mothay, Dipti [verfasserIn] Ramesh, K. V. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Coronavirus SARS-CoV-2 COVID-19 Protein homology modelling Molecular docking

Übergeordnetes Werk:	Enthalten in: Indian journal of virology - [New Delhi] : Springer India, 2010, 31(2020), 2 vom: 02. Mai, Seite 194-199
Übergeordnetes Werk:	volume:31 ; year:2020 ; number:2 ; day:02 ; month:05 ; pages:194-199

Links:	Volltext

DOI / URN:	10.1007/s13337-020-00585-z

Katalog-ID:	SPR040222020

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allfields	10.1007/s13337-020-00585-z doi (DE-627)SPR040222020 (SPR)s13337-020-00585-z-e DE-627 ger DE-627 rakwb eng 610 ASE Mothay, Dipti verfasserin aut Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Coronavirus (dpeaa)DE-He213 SARS-CoV-2 (dpeaa)DE-He213 COVID-19 (dpeaa)DE-He213 Protein homology modelling (dpeaa)DE-He213 Molecular docking (dpeaa)DE-He213 Ramesh, K. V. verfasserin aut Enthalten in Indian journal of virology [New Delhi] : Springer India, 2010 31(2020), 2 vom: 02. Mai, Seite 194-199 (DE-627)635133717 (DE-600)2572261-X 0974-0120 nnns volume:31 year:2020 number:2 day:02 month:05 pages:194-199 https://dx.doi.org/10.1007/s13337-020-00585-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_70 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 AR 31 2020 2 02 05 194-199
spelling	10.1007/s13337-020-00585-z doi (DE-627)SPR040222020 (SPR)s13337-020-00585-z-e DE-627 ger DE-627 rakwb eng 610 ASE Mothay, Dipti verfasserin aut Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Coronavirus (dpeaa)DE-He213 SARS-CoV-2 (dpeaa)DE-He213 COVID-19 (dpeaa)DE-He213 Protein homology modelling (dpeaa)DE-He213 Molecular docking (dpeaa)DE-He213 Ramesh, K. V. verfasserin aut Enthalten in Indian journal of virology [New Delhi] : Springer India, 2010 31(2020), 2 vom: 02. Mai, Seite 194-199 (DE-627)635133717 (DE-600)2572261-X 0974-0120 nnns volume:31 year:2020 number:2 day:02 month:05 pages:194-199 https://dx.doi.org/10.1007/s13337-020-00585-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_70 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 AR 31 2020 2 02 05 194-199
allfields_unstemmed	10.1007/s13337-020-00585-z doi (DE-627)SPR040222020 (SPR)s13337-020-00585-z-e DE-627 ger DE-627 rakwb eng 610 ASE Mothay, Dipti verfasserin aut Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Coronavirus (dpeaa)DE-He213 SARS-CoV-2 (dpeaa)DE-He213 COVID-19 (dpeaa)DE-He213 Protein homology modelling (dpeaa)DE-He213 Molecular docking (dpeaa)DE-He213 Ramesh, K. V. verfasserin aut Enthalten in Indian journal of virology [New Delhi] : Springer India, 2010 31(2020), 2 vom: 02. Mai, Seite 194-199 (DE-627)635133717 (DE-600)2572261-X 0974-0120 nnns volume:31 year:2020 number:2 day:02 month:05 pages:194-199 https://dx.doi.org/10.1007/s13337-020-00585-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_70 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 AR 31 2020 2 02 05 194-199
allfieldsGer	10.1007/s13337-020-00585-z doi (DE-627)SPR040222020 (SPR)s13337-020-00585-z-e DE-627 ger DE-627 rakwb eng 610 ASE Mothay, Dipti verfasserin aut Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Coronavirus (dpeaa)DE-He213 SARS-CoV-2 (dpeaa)DE-He213 COVID-19 (dpeaa)DE-He213 Protein homology modelling (dpeaa)DE-He213 Molecular docking (dpeaa)DE-He213 Ramesh, K. V. verfasserin aut Enthalten in Indian journal of virology [New Delhi] : Springer India, 2010 31(2020), 2 vom: 02. Mai, Seite 194-199 (DE-627)635133717 (DE-600)2572261-X 0974-0120 nnns volume:31 year:2020 number:2 day:02 month:05 pages:194-199 https://dx.doi.org/10.1007/s13337-020-00585-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_70 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 AR 31 2020 2 02 05 194-199
allfieldsSound	10.1007/s13337-020-00585-z doi (DE-627)SPR040222020 (SPR)s13337-020-00585-z-e DE-627 ger DE-627 rakwb eng 610 ASE Mothay, Dipti verfasserin aut Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract 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. Coronavirus (dpeaa)DE-He213 SARS-CoV-2 (dpeaa)DE-He213 COVID-19 (dpeaa)DE-He213 Protein homology modelling (dpeaa)DE-He213 Molecular docking (dpeaa)DE-He213 Ramesh, K. V. verfasserin aut Enthalten in Indian journal of virology [New Delhi] : Springer India, 2010 31(2020), 2 vom: 02. Mai, Seite 194-199 (DE-627)635133717 (DE-600)2572261-X 0974-0120 nnns volume:31 year:2020 number:2 day:02 month:05 pages:194-199 https://dx.doi.org/10.1007/s13337-020-00585-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_70 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 AR 31 2020 2 02 05 194-199
language	English
source	Enthalten in Indian journal of virology 31(2020), 2 vom: 02. Mai, Seite 194-199 volume:31 year:2020 number:2 day:02 month:05 pages:194-199
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topic_facet	Coronavirus SARS-CoV-2 COVID-19 Protein homology modelling Molecular docking
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author	Mothay, Dipti
spellingShingle	Mothay, Dipti ddc 610 misc Coronavirus misc SARS-CoV-2 misc COVID-19 misc Protein homology modelling misc Molecular docking Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
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topic_title	610 ASE Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock Coronavirus (dpeaa)DE-He213 SARS-CoV-2 (dpeaa)DE-He213 COVID-19 (dpeaa)DE-He213 Protein homology modelling (dpeaa)DE-He213 Molecular docking (dpeaa)DE-He213
topic	ddc 610 misc Coronavirus misc SARS-CoV-2 misc COVID-19 misc Protein homology modelling misc Molecular docking
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title	Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
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title_full	Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
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title_sort	binding site analysis of potential protease inhibitors of covid-19 using autodock
title_auth	Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
abstract	Abstract 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.
abstractGer	Abstract 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.
abstract_unstemmed	Abstract 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.
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title_short	Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock
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Binding site analysis of potential protease inhibitors of COVID-19 using AutoDock

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Zugang & Verfügbarkeit

Vorhandene Bände

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