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In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing
BACKGROUND: The rapidly enlarging COVID-19 pandemic caused by the novel SARS-corona virus-2 is a global public health emergency of an unprecedented level. Unfortunately no treatment therapy or vaccine is yet available to counter the SARS-CoV-2 infection, which substantiates the need to expand resear...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297718/ https://www.ncbi.nlm.nih.gov/pubmed/32561274 http://dx.doi.org/10.1016/j.jiph.2020.06.016 |
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author | Kumar, Yogesh Singh, Harvijay Patel, Chirag N. |
author_facet | Kumar, Yogesh Singh, Harvijay Patel, Chirag N. |
author_sort | Kumar, Yogesh |
collection | PubMed |
description | BACKGROUND: The rapidly enlarging COVID-19 pandemic caused by the novel SARS-corona virus-2 is a global public health emergency of an unprecedented level. Unfortunately no treatment therapy or vaccine is yet available to counter the SARS-CoV-2 infection, which substantiates the need to expand research efforts in this direction. The indispensable function of the main protease in virus replication makes this enzyme a promising target for inhibitors screening and drug discovery to treat novel coronavirus infection. The recently concluded α-ketoamide ligand-bound X-ray crystal structure of SARS-CoV-2 M(pro) (PDB ID: 6Y2F) from Zhang et al. has revealed the potential inhibitor binding mechanism and the molecular determinants responsible for substrate binding. METHODS: For the study, we have targeted the SARS-CoV-2 M(pro) for the screening of FDA approved antiviral drugs and carried out molecular docking based virtual screening. Further molecular dynamic simulation studies of the top three selected drugs carried out to investigated for their binding affinity and stability in the SARS-CoV-2 M(pro) active site. The phylogenetic analysis was also performed to know the relatedness between the SARS-CoV-2 genomes isolated from different countries. RESULTS: The phylogenetic analysis of the SARS-CoV-2 genome reveals that the virus is closely related to the Bat-SL-CoV and does not exhibit any divergence at the genomic level. Molecular docking studies revealed that among the 77 drugs, screened top ten drugs shows good binding affinities, whereas the top three drugs: Lopinavir–Ritonavir, Tipranavir, and Raltegravir were undergone for molecular dynamics simulation studies for their conformational stability in the active site of the SARS-CoV-2 M(pro) protein. CONCLUSIONS: In the present study among the library of FDA approved antiviral drugs, the top three inhibitors Lopinavir–Ritonavir, Tipranavir, and Raltegravir show the best molecular interaction with the main protease of SARS-CoV-2. However, the in-vitro efficacy of the drug molecules screened in this study further needs to be corroborated by carrying out a biochemical and structural investigation. |
format | Online Article Text |
id | pubmed-7297718 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72977182020-06-17 In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing Kumar, Yogesh Singh, Harvijay Patel, Chirag N. J Infect Public Health Original Article BACKGROUND: The rapidly enlarging COVID-19 pandemic caused by the novel SARS-corona virus-2 is a global public health emergency of an unprecedented level. Unfortunately no treatment therapy or vaccine is yet available to counter the SARS-CoV-2 infection, which substantiates the need to expand research efforts in this direction. The indispensable function of the main protease in virus replication makes this enzyme a promising target for inhibitors screening and drug discovery to treat novel coronavirus infection. The recently concluded α-ketoamide ligand-bound X-ray crystal structure of SARS-CoV-2 M(pro) (PDB ID: 6Y2F) from Zhang et al. has revealed the potential inhibitor binding mechanism and the molecular determinants responsible for substrate binding. METHODS: For the study, we have targeted the SARS-CoV-2 M(pro) for the screening of FDA approved antiviral drugs and carried out molecular docking based virtual screening. Further molecular dynamic simulation studies of the top three selected drugs carried out to investigated for their binding affinity and stability in the SARS-CoV-2 M(pro) active site. The phylogenetic analysis was also performed to know the relatedness between the SARS-CoV-2 genomes isolated from different countries. RESULTS: The phylogenetic analysis of the SARS-CoV-2 genome reveals that the virus is closely related to the Bat-SL-CoV and does not exhibit any divergence at the genomic level. Molecular docking studies revealed that among the 77 drugs, screened top ten drugs shows good binding affinities, whereas the top three drugs: Lopinavir–Ritonavir, Tipranavir, and Raltegravir were undergone for molecular dynamics simulation studies for their conformational stability in the active site of the SARS-CoV-2 M(pro) protein. CONCLUSIONS: In the present study among the library of FDA approved antiviral drugs, the top three inhibitors Lopinavir–Ritonavir, Tipranavir, and Raltegravir show the best molecular interaction with the main protease of SARS-CoV-2. However, the in-vitro efficacy of the drug molecules screened in this study further needs to be corroborated by carrying out a biochemical and structural investigation. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2020-09 2020-06-16 /pmc/articles/PMC7297718/ /pubmed/32561274 http://dx.doi.org/10.1016/j.jiph.2020.06.016 Text en © 2020 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 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 | Original Article Kumar, Yogesh Singh, Harvijay Patel, Chirag N. In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing |
title | In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing |
title_full | In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing |
title_fullStr | In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing |
title_full_unstemmed | In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing |
title_short | In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing |
title_sort | in silico prediction of potential inhibitors for the main protease of sars-cov-2 using molecular docking and dynamics simulation based drug-repurposing |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297718/ https://www.ncbi.nlm.nih.gov/pubmed/32561274 http://dx.doi.org/10.1016/j.jiph.2020.06.016 |
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