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Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions

CONTEXT: Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs...

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Autores principales: Li, Bo, Guo, Jindan, Hu, Wenxiang, Chen, Yubao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123576/
https://www.ncbi.nlm.nih.gov/pubmed/37093365
http://dx.doi.org/10.1007/s00894-023-05536-1
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author Li, Bo
Guo, Jindan
Hu, Wenxiang
Chen, Yubao
author_facet Li, Bo
Guo, Jindan
Hu, Wenxiang
Chen, Yubao
author_sort Li, Bo
collection PubMed
description CONTEXT: Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs and vaccines, making the epidemic significantly difficult to prevent and control, and seriously threaten health around the world. Importunately exploration of mutant characteristics for novel coronavirus Omicron can supply strong theoretical guidance for learning binding mechanism of mutant viruses. What’s more, full acknowledgement of key mutated-residues on Omicron strain can provide new methodology of the novel pathogenic mechanism to human ACE2 receptor, as well as the subsequent vaccine development. METHODS: In this research, 3D structures of 32 single-point mutations of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron were finally obtained based one the wild-type virus by homology modeling method. One total number of 33 2019-nCov/ACE2 complex systems were acquired by protein-protein docking, and optimized by using preliminary molecular dynamic simulations. Binding free energies between each 2019-nCov mutation system and human ACE2 receptor were calculated, and corresponding binding patterns especially the regions adjacent to mutation site were analyzed. The results indicated that one total number of 6 mutated sites on the Omicron strain played crucial role in improving binding capacities from 2019-nCov to ACE2 protein. Subsequently, we performed long-term molecular dynamic simulations and protein-protein binding energy analysis for the selected 6 mutations. 3 infected individuals, the mutants T478K, Q493R and G496S with lower binding energies -66.36, -67.98 and -67.09 kcal/mol also presents the high infectivity. These findings indicated that the 3 mutations T478K, Q493R and G496S play the crucial roles in enhancing binding affinity of Omicron to human ACE2 protein. All these results illuminate important theoretical guidance for future virus detection of the Omicron epidemic, drug research and vaccine development.
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spelling pubmed-101235762023-04-25 Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions Li, Bo Guo, Jindan Hu, Wenxiang Chen, Yubao J Mol Model Original Paper CONTEXT: Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs and vaccines, making the epidemic significantly difficult to prevent and control, and seriously threaten health around the world. Importunately exploration of mutant characteristics for novel coronavirus Omicron can supply strong theoretical guidance for learning binding mechanism of mutant viruses. What’s more, full acknowledgement of key mutated-residues on Omicron strain can provide new methodology of the novel pathogenic mechanism to human ACE2 receptor, as well as the subsequent vaccine development. METHODS: In this research, 3D structures of 32 single-point mutations of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron were finally obtained based one the wild-type virus by homology modeling method. One total number of 33 2019-nCov/ACE2 complex systems were acquired by protein-protein docking, and optimized by using preliminary molecular dynamic simulations. Binding free energies between each 2019-nCov mutation system and human ACE2 receptor were calculated, and corresponding binding patterns especially the regions adjacent to mutation site were analyzed. The results indicated that one total number of 6 mutated sites on the Omicron strain played crucial role in improving binding capacities from 2019-nCov to ACE2 protein. Subsequently, we performed long-term molecular dynamic simulations and protein-protein binding energy analysis for the selected 6 mutations. 3 infected individuals, the mutants T478K, Q493R and G496S with lower binding energies -66.36, -67.98 and -67.09 kcal/mol also presents the high infectivity. These findings indicated that the 3 mutations T478K, Q493R and G496S play the crucial roles in enhancing binding affinity of Omicron to human ACE2 protein. All these results illuminate important theoretical guidance for future virus detection of the Omicron epidemic, drug research and vaccine development. Springer Berlin Heidelberg 2023-04-24 2023 /pmc/articles/PMC10123576/ /pubmed/37093365 http://dx.doi.org/10.1007/s00894-023-05536-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Li, Bo
Guo, Jindan
Hu, Wenxiang
Chen, Yubao
Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
title Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
title_full Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
title_fullStr Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
title_full_unstemmed Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
title_short Binding affinity improvement analysis of multiple-mutant Omicron on 2019-nCov to human ACE2 by in silico predictions
title_sort binding affinity improvement analysis of multiple-mutant omicron on 2019-ncov to human ace2 by in silico predictions
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123576/
https://www.ncbi.nlm.nih.gov/pubmed/37093365
http://dx.doi.org/10.1007/s00894-023-05536-1
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