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A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection

The emergence of the novel SARS-CoV-2 virus is the most important public-health issue of our time. Understanding the diverse clinical presentations of the ensuing disease, COVID-19, remains a critical unmet need. Here we present a comprehensive listing of the diverse clinical indications associated...

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Autores principales: McGill, Joseph R., Lagassé, H. A. Daniel, Hernandez, Nancy, Hopkins, Louis, Jankowski, Wojciech, McCormick, Quinn, Simhadri, Vijaya, Golding, Basil, Sauna, Zuben E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259575/
https://www.ncbi.nlm.nih.gov/pubmed/35794133
http://dx.doi.org/10.1038/s41598-022-15225-3
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author McGill, Joseph R.
Lagassé, H. A. Daniel
Hernandez, Nancy
Hopkins, Louis
Jankowski, Wojciech
McCormick, Quinn
Simhadri, Vijaya
Golding, Basil
Sauna, Zuben E.
author_facet McGill, Joseph R.
Lagassé, H. A. Daniel
Hernandez, Nancy
Hopkins, Louis
Jankowski, Wojciech
McCormick, Quinn
Simhadri, Vijaya
Golding, Basil
Sauna, Zuben E.
author_sort McGill, Joseph R.
collection PubMed
description The emergence of the novel SARS-CoV-2 virus is the most important public-health issue of our time. Understanding the diverse clinical presentations of the ensuing disease, COVID-19, remains a critical unmet need. Here we present a comprehensive listing of the diverse clinical indications associated with COVID-19. We explore the theory that anti-SARS-CoV-2 antibodies could cross-react with endogenous human proteins driving some of the pathologies associated with COVID-19. We describe a novel computational approach to estimate structural homology between SARS-CoV-2 proteins and human proteins. Antibodies are more likely to interrogate 3D-structural epitopes than continuous linear epitopes. This computational workflow identified 346 human proteins containing a domain with high structural homology to a SARS-CoV-2 Wuhan strain protein. Of these, 102 proteins exhibit functions that could contribute to COVID-19 clinical pathologies. We present a testable hypothesis to delineate unexplained clinical observations vis-à-vis COVID-19 and a tool to evaluate the safety-risk profile of potential COVID-19 therapies.
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spelling pubmed-92595752022-07-08 A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection McGill, Joseph R. Lagassé, H. A. Daniel Hernandez, Nancy Hopkins, Louis Jankowski, Wojciech McCormick, Quinn Simhadri, Vijaya Golding, Basil Sauna, Zuben E. Sci Rep Article The emergence of the novel SARS-CoV-2 virus is the most important public-health issue of our time. Understanding the diverse clinical presentations of the ensuing disease, COVID-19, remains a critical unmet need. Here we present a comprehensive listing of the diverse clinical indications associated with COVID-19. We explore the theory that anti-SARS-CoV-2 antibodies could cross-react with endogenous human proteins driving some of the pathologies associated with COVID-19. We describe a novel computational approach to estimate structural homology between SARS-CoV-2 proteins and human proteins. Antibodies are more likely to interrogate 3D-structural epitopes than continuous linear epitopes. This computational workflow identified 346 human proteins containing a domain with high structural homology to a SARS-CoV-2 Wuhan strain protein. Of these, 102 proteins exhibit functions that could contribute to COVID-19 clinical pathologies. We present a testable hypothesis to delineate unexplained clinical observations vis-à-vis COVID-19 and a tool to evaluate the safety-risk profile of potential COVID-19 therapies. Nature Publishing Group UK 2022-07-06 /pmc/articles/PMC9259575/ /pubmed/35794133 http://dx.doi.org/10.1038/s41598-022-15225-3 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 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
McGill, Joseph R.
Lagassé, H. A. Daniel
Hernandez, Nancy
Hopkins, Louis
Jankowski, Wojciech
McCormick, Quinn
Simhadri, Vijaya
Golding, Basil
Sauna, Zuben E.
A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection
title A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection
title_full A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection
title_fullStr A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection
title_full_unstemmed A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection
title_short A structural homology approach to identify potential cross-reactive antibody responses following SARS-CoV-2 infection
title_sort structural homology approach to identify potential cross-reactive antibody responses following sars-cov-2 infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259575/
https://www.ncbi.nlm.nih.gov/pubmed/35794133
http://dx.doi.org/10.1038/s41598-022-15225-3
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