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Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion

Given the COVID-19 pandemic, there is interest in understanding ligand-receptor features and targeted antibody-binding attributes against emerging SARS-CoV-2 variants. Here, we developed a large-scale structure-based pipeline for analysis of protein-protein interactions regulating SARS-CoV-2 immune...

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Autores principales: Lubin, Joseph H., Markosian, Christopher, Balamurugan, D., Ma, Minh T., Chen, Chih-Hsiung, Liu, Dongfang, Pasqualini, Renata, Arap, Wadih, Burley, Stephen K., Khare, Sagar D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Clinical Investigation 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371346/
https://www.ncbi.nlm.nih.gov/pubmed/37261904
http://dx.doi.org/10.1172/jci.insight.168296
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author Lubin, Joseph H.
Markosian, Christopher
Balamurugan, D.
Ma, Minh T.
Chen, Chih-Hsiung
Liu, Dongfang
Pasqualini, Renata
Arap, Wadih
Burley, Stephen K.
Khare, Sagar D.
author_facet Lubin, Joseph H.
Markosian, Christopher
Balamurugan, D.
Ma, Minh T.
Chen, Chih-Hsiung
Liu, Dongfang
Pasqualini, Renata
Arap, Wadih
Burley, Stephen K.
Khare, Sagar D.
author_sort Lubin, Joseph H.
collection PubMed
description Given the COVID-19 pandemic, there is interest in understanding ligand-receptor features and targeted antibody-binding attributes against emerging SARS-CoV-2 variants. Here, we developed a large-scale structure-based pipeline for analysis of protein-protein interactions regulating SARS-CoV-2 immune evasion. First, we generated computed structural models of the Spike protein of 3 SARS-CoV-2 variants (B.1.1.529, BA.2.12.1, and BA.5) bound either to a native receptor (ACE2) or to a large panel of targeted ligands (n = 282), which included neutralizing or therapeutic monoclonal antibodies. Moreover, by using the Barnes classification, we noted an overall loss of interfacial interactions (with gain of new interactions in certain cases) at the receptor-binding domain (RBD) mediated by substituted residues for neutralizing complexes in classes 1 and 2, whereas less destabilization was observed for classes 3 and 4. Finally, an experimental validation of predicted weakened therapeutic antibody binding was performed in a cell-based assay. Compared with the original Omicron variant (B.1.1.529), derivative variants featured progressive destabilization of antibody-RBD interfaces mediated by a larger set of substituted residues, thereby providing a molecular basis for immune evasion. This approach and findings provide a framework for rapidly and efficiently generating structural models for SARS-CoV-2 variants bound to ligands of mechanistic and therapeutic value.
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spelling pubmed-103713462023-07-27 Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion Lubin, Joseph H. Markosian, Christopher Balamurugan, D. Ma, Minh T. Chen, Chih-Hsiung Liu, Dongfang Pasqualini, Renata Arap, Wadih Burley, Stephen K. Khare, Sagar D. JCI Insight Research Article Given the COVID-19 pandemic, there is interest in understanding ligand-receptor features and targeted antibody-binding attributes against emerging SARS-CoV-2 variants. Here, we developed a large-scale structure-based pipeline for analysis of protein-protein interactions regulating SARS-CoV-2 immune evasion. First, we generated computed structural models of the Spike protein of 3 SARS-CoV-2 variants (B.1.1.529, BA.2.12.1, and BA.5) bound either to a native receptor (ACE2) or to a large panel of targeted ligands (n = 282), which included neutralizing or therapeutic monoclonal antibodies. Moreover, by using the Barnes classification, we noted an overall loss of interfacial interactions (with gain of new interactions in certain cases) at the receptor-binding domain (RBD) mediated by substituted residues for neutralizing complexes in classes 1 and 2, whereas less destabilization was observed for classes 3 and 4. Finally, an experimental validation of predicted weakened therapeutic antibody binding was performed in a cell-based assay. Compared with the original Omicron variant (B.1.1.529), derivative variants featured progressive destabilization of antibody-RBD interfaces mediated by a larger set of substituted residues, thereby providing a molecular basis for immune evasion. This approach and findings provide a framework for rapidly and efficiently generating structural models for SARS-CoV-2 variants bound to ligands of mechanistic and therapeutic value. American Society for Clinical Investigation 2023-07-10 /pmc/articles/PMC10371346/ /pubmed/37261904 http://dx.doi.org/10.1172/jci.insight.168296 Text en © 2023 Lubin et al. https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Lubin, Joseph H.
Markosian, Christopher
Balamurugan, D.
Ma, Minh T.
Chen, Chih-Hsiung
Liu, Dongfang
Pasqualini, Renata
Arap, Wadih
Burley, Stephen K.
Khare, Sagar D.
Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion
title Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion
title_full Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion
title_fullStr Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion
title_full_unstemmed Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion
title_short Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion
title_sort modeling of ace2 and antibodies bound to sars-cov-2 provides insights into infectivity and immune evasion
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371346/
https://www.ncbi.nlm.nih.gov/pubmed/37261904
http://dx.doi.org/10.1172/jci.insight.168296
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