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Candidate Binding Sites for Allosteric Inhibition of the SARS-CoV-2 Main Protease from the Analysis of Large-Scale Molecular Dynamics Simulations
[Image: see text] We analyzed a 100 μs MD trajectory of the SARS-CoV-2 main protease by a non-parametric data analysis approach which allows characterizing a free energy landscape as a simultaneous function of hundreds of variables. We identified several conformations that, when visited by the dynam...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755075/ https://www.ncbi.nlm.nih.gov/pubmed/33306377 http://dx.doi.org/10.1021/acs.jpclett.0c03182 |
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author | Carli, Matteo Sormani, Giulia Rodriguez, Alex Laio, Alessandro |
author_facet | Carli, Matteo Sormani, Giulia Rodriguez, Alex Laio, Alessandro |
author_sort | Carli, Matteo |
collection | PubMed |
description | [Image: see text] We analyzed a 100 μs MD trajectory of the SARS-CoV-2 main protease by a non-parametric data analysis approach which allows characterizing a free energy landscape as a simultaneous function of hundreds of variables. We identified several conformations that, when visited by the dynamics, are stable for several hundred nanoseconds. We explicitly characterize and describe these metastable states. In some of these configurations, the catalytic dyad is less accessible. Stabilizing them by a suitable binder could lead to an inhibition of the enzymatic activity. In our analysis we keep track of relevant contacts between residues which are selectively broken or formed in the states. Some of these contacts are formed by residues which are far from the catalytic dyad and are accessible to the solvent. Based on this analysis we propose some relevant contact patterns and three possible binding sites which could be targeted to achieve allosteric inhibition. |
format | Online Article Text |
id | pubmed-7755075 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-77550752020-12-22 Candidate Binding Sites for Allosteric Inhibition of the SARS-CoV-2 Main Protease from the Analysis of Large-Scale Molecular Dynamics Simulations Carli, Matteo Sormani, Giulia Rodriguez, Alex Laio, Alessandro J Phys Chem Lett [Image: see text] We analyzed a 100 μs MD trajectory of the SARS-CoV-2 main protease by a non-parametric data analysis approach which allows characterizing a free energy landscape as a simultaneous function of hundreds of variables. We identified several conformations that, when visited by the dynamics, are stable for several hundred nanoseconds. We explicitly characterize and describe these metastable states. In some of these configurations, the catalytic dyad is less accessible. Stabilizing them by a suitable binder could lead to an inhibition of the enzymatic activity. In our analysis we keep track of relevant contacts between residues which are selectively broken or formed in the states. Some of these contacts are formed by residues which are far from the catalytic dyad and are accessible to the solvent. Based on this analysis we propose some relevant contact patterns and three possible binding sites which could be targeted to achieve allosteric inhibition. American Chemical Society 2020-12-11 2021-01-14 /pmc/articles/PMC7755075/ /pubmed/33306377 http://dx.doi.org/10.1021/acs.jpclett.0c03182 Text en © 2020 American Chemical Society Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Carli, Matteo Sormani, Giulia Rodriguez, Alex Laio, Alessandro Candidate Binding Sites for Allosteric Inhibition of the SARS-CoV-2 Main Protease from the Analysis of Large-Scale Molecular Dynamics Simulations |
title | Candidate Binding Sites for Allosteric Inhibition
of the SARS-CoV-2 Main
Protease from the Analysis of Large-Scale Molecular Dynamics Simulations |
title_full | Candidate Binding Sites for Allosteric Inhibition
of the SARS-CoV-2 Main
Protease from the Analysis of Large-Scale Molecular Dynamics Simulations |
title_fullStr | Candidate Binding Sites for Allosteric Inhibition
of the SARS-CoV-2 Main
Protease from the Analysis of Large-Scale Molecular Dynamics Simulations |
title_full_unstemmed | Candidate Binding Sites for Allosteric Inhibition
of the SARS-CoV-2 Main
Protease from the Analysis of Large-Scale Molecular Dynamics Simulations |
title_short | Candidate Binding Sites for Allosteric Inhibition
of the SARS-CoV-2 Main
Protease from the Analysis of Large-Scale Molecular Dynamics Simulations |
title_sort | candidate binding sites for allosteric inhibition
of the sars-cov-2 main
protease from the analysis of large-scale molecular dynamics simulations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755075/ https://www.ncbi.nlm.nih.gov/pubmed/33306377 http://dx.doi.org/10.1021/acs.jpclett.0c03182 |
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