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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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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. |
format | Online Article Text |
id | pubmed-9259575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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