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Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations
The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790385/ https://www.ncbi.nlm.nih.gov/pubmed/35116157 http://dx.doi.org/10.1098/rsos.211480 |
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author | Tam, Nguyen Minh Nguyen, Trung Hai Ngan, Vu Thi Tung, Nguyen Thanh Ngo, Son Tung |
author_facet | Tam, Nguyen Minh Nguyen, Trung Hai Ngan, Vu Thi Tung, Nguyen Thanh Ngo, Son Tung |
author_sort | Tam, Nguyen Minh |
collection | PubMed |
description | The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand (FPL) methods. In detail, the correlation coefficient between US and experiments does not differ from FPL and is slightly smaller than LIE. The root mean square error of US simulations is smaller than that of LIE. Moreover, US is better than FPL and poorer than LIE in classifying SARS-CoV-2 Mpro inhibitors owing to the reciever operating characteristic–area under the curve analysis. Furthermore, the US simulations also provide detailed insights on unbinding pathways of ligands from the binding cleft of SARS-CoV-2 Mpro. The residues Cys44, Thr45, Ser46, Leu141, Asn142, Gly143, Glu166, Leu167, Pro168, Ala191, Gln192 and Ala193 probably play an important role in the ligand dissociation. Therefore, substitutions at these points may change the mechanism of binding of inhibitors to SARS-CoV-2 Mpro. |
format | Online Article Text |
id | pubmed-8790385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-87903852022-02-02 Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations Tam, Nguyen Minh Nguyen, Trung Hai Ngan, Vu Thi Tung, Nguyen Thanh Ngo, Son Tung R Soc Open Sci Chemistry The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand (FPL) methods. In detail, the correlation coefficient between US and experiments does not differ from FPL and is slightly smaller than LIE. The root mean square error of US simulations is smaller than that of LIE. Moreover, US is better than FPL and poorer than LIE in classifying SARS-CoV-2 Mpro inhibitors owing to the reciever operating characteristic–area under the curve analysis. Furthermore, the US simulations also provide detailed insights on unbinding pathways of ligands from the binding cleft of SARS-CoV-2 Mpro. The residues Cys44, Thr45, Ser46, Leu141, Asn142, Gly143, Glu166, Leu167, Pro168, Ala191, Gln192 and Ala193 probably play an important role in the ligand dissociation. Therefore, substitutions at these points may change the mechanism of binding of inhibitors to SARS-CoV-2 Mpro. The Royal Society 2022-01-26 /pmc/articles/PMC8790385/ /pubmed/35116157 http://dx.doi.org/10.1098/rsos.211480 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Chemistry Tam, Nguyen Minh Nguyen, Trung Hai Ngan, Vu Thi Tung, Nguyen Thanh Ngo, Son Tung Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations |
title | Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations |
title_full | Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations |
title_fullStr | Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations |
title_full_unstemmed | Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations |
title_short | Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations |
title_sort | unbinding ligands from sars-cov-2 mpro via umbrella sampling simulations |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790385/ https://www.ncbi.nlm.nih.gov/pubmed/35116157 http://dx.doi.org/10.1098/rsos.211480 |
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