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Interaction Analysis of the Spike Protein of Delta and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal Antibodies Using the Fragment Molecular Orbital Method
[Image: see text] In the past 2 years, since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple SARS-CoV-2 variants have emerged. Whenever a new variant emerges, considerable time is required to analyze the binding affinity of the viral surface proteins to human...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982492/ https://www.ncbi.nlm.nih.gov/pubmed/35312321 http://dx.doi.org/10.1021/acs.jcim.2c00100 |
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author | Hwang, Sungbo Baek, Seung-Hwa Park, Daeui |
author_facet | Hwang, Sungbo Baek, Seung-Hwa Park, Daeui |
author_sort | Hwang, Sungbo |
collection | PubMed |
description | [Image: see text] In the past 2 years, since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple SARS-CoV-2 variants have emerged. Whenever a new variant emerges, considerable time is required to analyze the binding affinity of the viral surface proteins to human angiotensin-converting enzyme 2 (hACE2) and monoclonal antibodies. To efficiently predict the binding affinities associated with hACE2 and monoclonal antibodies in a short time, herein, we propose a method applying statistical analysis to simulations performed using molecular and quantum mechanics. This method efficiently predicted the trend of binding affinity for the binding of the spike protein of each variant of SARS-CoV-2 to hACE2 and individually to eight commercial monoclonal antibodies. Additionally, this method accurately predicted interaction energy changes in the crystal structure for 10 of 13 mutated residues in the Omicron variant, showing a significant change in the interaction energy of hACE2. S375F was found to be a mutation that majorly changed the binding affinity of the spike protein to hACE2 and the eight monoclonal antibodies. Our proposed analysis method enables the prediction of the binding affinity of new variants to hACE2 or to monoclonal antibodies in a shorter time compared to that utilized by the experimental method. |
format | Online Article Text |
id | pubmed-8982492 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-89824922022-04-05 Interaction Analysis of the Spike Protein of Delta and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal Antibodies Using the Fragment Molecular Orbital Method Hwang, Sungbo Baek, Seung-Hwa Park, Daeui J Chem Inf Model [Image: see text] In the past 2 years, since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple SARS-CoV-2 variants have emerged. Whenever a new variant emerges, considerable time is required to analyze the binding affinity of the viral surface proteins to human angiotensin-converting enzyme 2 (hACE2) and monoclonal antibodies. To efficiently predict the binding affinities associated with hACE2 and monoclonal antibodies in a short time, herein, we propose a method applying statistical analysis to simulations performed using molecular and quantum mechanics. This method efficiently predicted the trend of binding affinity for the binding of the spike protein of each variant of SARS-CoV-2 to hACE2 and individually to eight commercial monoclonal antibodies. Additionally, this method accurately predicted interaction energy changes in the crystal structure for 10 of 13 mutated residues in the Omicron variant, showing a significant change in the interaction energy of hACE2. S375F was found to be a mutation that majorly changed the binding affinity of the spike protein to hACE2 and the eight monoclonal antibodies. Our proposed analysis method enables the prediction of the binding affinity of new variants to hACE2 or to monoclonal antibodies in a shorter time compared to that utilized by the experimental method. American Chemical Society 2022-03-21 2022-04-11 /pmc/articles/PMC8982492/ /pubmed/35312321 http://dx.doi.org/10.1021/acs.jcim.2c00100 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Hwang, Sungbo Baek, Seung-Hwa Park, Daeui Interaction Analysis of the Spike Protein of Delta and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal Antibodies Using the Fragment Molecular Orbital Method |
title | Interaction Analysis of the Spike Protein of Delta
and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal
Antibodies Using the Fragment Molecular Orbital Method |
title_full | Interaction Analysis of the Spike Protein of Delta
and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal
Antibodies Using the Fragment Molecular Orbital Method |
title_fullStr | Interaction Analysis of the Spike Protein of Delta
and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal
Antibodies Using the Fragment Molecular Orbital Method |
title_full_unstemmed | Interaction Analysis of the Spike Protein of Delta
and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal
Antibodies Using the Fragment Molecular Orbital Method |
title_short | Interaction Analysis of the Spike Protein of Delta
and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal
Antibodies Using the Fragment Molecular Orbital Method |
title_sort | interaction analysis of the spike protein of delta
and omicron variants of sars-cov-2 with hace2 and eight monoclonal
antibodies using the fragment molecular orbital method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982492/ https://www.ncbi.nlm.nih.gov/pubmed/35312321 http://dx.doi.org/10.1021/acs.jcim.2c00100 |
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