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Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor

SARS-CoV-2 is coronavirus causing COVID-19 pandemic. To enter human cells, receptor binding domain of S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) binds to peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptor. Employing peptides to inhibit binding between SARS-CoV-2-RBD and ACE2-PD...

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Autores principales: Sitthiyotha, Thassanai, Chunsrivirot, Surasak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329052/
https://www.ncbi.nlm.nih.gov/pubmed/34341401
http://dx.doi.org/10.1038/s41598-021-94873-3
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author Sitthiyotha, Thassanai
Chunsrivirot, Surasak
author_facet Sitthiyotha, Thassanai
Chunsrivirot, Surasak
author_sort Sitthiyotha, Thassanai
collection PubMed
description SARS-CoV-2 is coronavirus causing COVID-19 pandemic. To enter human cells, receptor binding domain of S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) binds to peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptor. Employing peptides to inhibit binding between SARS-CoV-2-RBD and ACE2-PD is a therapeutic solution for COVID-19. Previous experimental study found that 23-mer peptide (SBP1) bound to SARS-CoV-2-RBD with lower affinity than ACE2. To increase SBP1 affinity, our previous study used residues 21–45 of α1 helix of ACE2-PD (SPB25) to design peptides with predicted affinity better than SBP1 and SPB25 by increasing interactions of residues that do not form favorable interactions with SARS-CoV-2-RBD. To design SPB25 with better affinity than ACE2, we employed computational protein design to increase interactions of residues reported to form favorable interactions with SARS-CoV-2-RBD and combine newly designed mutations with the best single mutations from our previous study. Molecular dynamics show that predicted binding affinities of three peptides (SPB25(Q22R), SPB25(F8R/K11W/L25R) and SPB25(F8R/K11F/Q22R/L25R)) are better than ACE2. Moreover, their predicted stabilities may be slightly higher than SBP1 as suggested by their helicities. This study developed an approach to design SARS-CoV-2 peptide binders with predicted binding affinities better than ACE2. These designed peptides are promising candidates as SARS-CoV-2 inhibitors.
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spelling pubmed-83290522021-08-03 Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor Sitthiyotha, Thassanai Chunsrivirot, Surasak Sci Rep Article SARS-CoV-2 is coronavirus causing COVID-19 pandemic. To enter human cells, receptor binding domain of S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) binds to peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptor. Employing peptides to inhibit binding between SARS-CoV-2-RBD and ACE2-PD is a therapeutic solution for COVID-19. Previous experimental study found that 23-mer peptide (SBP1) bound to SARS-CoV-2-RBD with lower affinity than ACE2. To increase SBP1 affinity, our previous study used residues 21–45 of α1 helix of ACE2-PD (SPB25) to design peptides with predicted affinity better than SBP1 and SPB25 by increasing interactions of residues that do not form favorable interactions with SARS-CoV-2-RBD. To design SPB25 with better affinity than ACE2, we employed computational protein design to increase interactions of residues reported to form favorable interactions with SARS-CoV-2-RBD and combine newly designed mutations with the best single mutations from our previous study. Molecular dynamics show that predicted binding affinities of three peptides (SPB25(Q22R), SPB25(F8R/K11W/L25R) and SPB25(F8R/K11F/Q22R/L25R)) are better than ACE2. Moreover, their predicted stabilities may be slightly higher than SBP1 as suggested by their helicities. This study developed an approach to design SARS-CoV-2 peptide binders with predicted binding affinities better than ACE2. These designed peptides are promising candidates as SARS-CoV-2 inhibitors. Nature Publishing Group UK 2021-08-02 /pmc/articles/PMC8329052/ /pubmed/34341401 http://dx.doi.org/10.1038/s41598-021-94873-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Article
Sitthiyotha, Thassanai
Chunsrivirot, Surasak
Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor
title Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor
title_full Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor
title_fullStr Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor
title_full_unstemmed Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor
title_short Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor
title_sort computational design of sars-cov-2 peptide binders with better predicted binding affinities than human ace2 receptor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329052/
https://www.ncbi.nlm.nih.gov/pubmed/34341401
http://dx.doi.org/10.1038/s41598-021-94873-3
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