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In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection
CONTEXT: The unavailability of target-specific antiviral drugs for SARS-CoV-2 viral infection kindled the motivation to virtually design derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide as potential antiviral inhibitors against the concerned virus. The molecular docking and molecu...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10074334/ https://www.ncbi.nlm.nih.gov/pubmed/37017775 http://dx.doi.org/10.1007/s00894-023-05535-2 |
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author | Sinha, Prashasti Yadav, Anil Kumar |
author_facet | Sinha, Prashasti Yadav, Anil Kumar |
author_sort | Sinha, Prashasti |
collection | PubMed |
description | CONTEXT: The unavailability of target-specific antiviral drugs for SARS-CoV-2 viral infection kindled the motivation to virtually design derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide as potential antiviral inhibitors against the concerned virus. The molecular docking and molecular dynamic results revealed that the reported derivatives have a potential to act as antiviral drug against SARS-CoV-2. The reported hit compounds can be considered for in vitro and in vivo analyses. METHODS: Fragment-based drug designing was used to model the derivatives. Furthermore, DFT simulations were carried out using B3LYP/6-311G** basis set. Docking simulations were performed by using a combination of empirical free energy force field with a Lamarckian genetic algorithm under AutoDock 4.2. By the application of AMBER14 force field and SPCE water model, molecular dynamic simulations and MM-PBSA were calculated for 100 ns. |
format | Online Article Text |
id | pubmed-10074334 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-100743342023-04-05 In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection Sinha, Prashasti Yadav, Anil Kumar J Mol Model Original Paper CONTEXT: The unavailability of target-specific antiviral drugs for SARS-CoV-2 viral infection kindled the motivation to virtually design derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide as potential antiviral inhibitors against the concerned virus. The molecular docking and molecular dynamic results revealed that the reported derivatives have a potential to act as antiviral drug against SARS-CoV-2. The reported hit compounds can be considered for in vitro and in vivo analyses. METHODS: Fragment-based drug designing was used to model the derivatives. Furthermore, DFT simulations were carried out using B3LYP/6-311G** basis set. Docking simulations were performed by using a combination of empirical free energy force field with a Lamarckian genetic algorithm under AutoDock 4.2. By the application of AMBER14 force field and SPCE water model, molecular dynamic simulations and MM-PBSA were calculated for 100 ns. Springer Berlin Heidelberg 2023-04-05 2023 /pmc/articles/PMC10074334/ /pubmed/37017775 http://dx.doi.org/10.1007/s00894-023-05535-2 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 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 | Original Paper Sinha, Prashasti Yadav, Anil Kumar In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection |
title | In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection |
title_full | In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection |
title_fullStr | In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection |
title_full_unstemmed | In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection |
title_short | In silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3CL(pro) of SARS-CoV-2 viral infection |
title_sort | in silico identification and molecular dynamic simulations of derivatives of 6,6-dimethyl-3-azabicyclo[3.1.0]hexane-2-carboxamide against main protease 3cl(pro) of sars-cov-2 viral infection |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10074334/ https://www.ncbi.nlm.nih.gov/pubmed/37017775 http://dx.doi.org/10.1007/s00894-023-05535-2 |
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