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Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein
The SARS-CoV-2 outbreak originated in China in late 2019 and has since spread to pandemic proportions. Diagnostics, therapeutics and vaccines are urgently needed. We model the trimeric Spike protein, including flexible loops and all N-glycosylation sites, in order to elucidate accessible epitopes fo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474083/ https://www.ncbi.nlm.nih.gov/pubmed/32944295 http://dx.doi.org/10.1038/s41541-020-00237-9 |
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author | Wintjens, René Bifani, Amanda Makha Bifani, Pablo |
author_facet | Wintjens, René Bifani, Amanda Makha Bifani, Pablo |
author_sort | Wintjens, René |
collection | PubMed |
description | The SARS-CoV-2 outbreak originated in China in late 2019 and has since spread to pandemic proportions. Diagnostics, therapeutics and vaccines are urgently needed. We model the trimeric Spike protein, including flexible loops and all N-glycosylation sites, in order to elucidate accessible epitopes for antibody-based diagnostics, therapeutics and vaccine development. Based on published experimental data, six homogeneous glycosylation patterns and two heterogeneous ones were used for the analysis. The glycan chains alter the accessible surface areas on the S-protein, impeding antibody-antigen recognition. In presence of glycan, epitopes on the S1 subunit, that notably contains the receptor binding domain, remain mostly accessible to antibodies while those present on the S2 subunit are predominantly inaccessible. We identify 28 B-cell epitopes in the Spike structure and group them as non-affected by the glycan cloud versus those which are strongly masked by the glycan cloud, resulting in a list of favourable epitopes as targets for vaccine development, antibody-based therapy and diagnostics. |
format | Online Article Text |
id | pubmed-7474083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74740832020-09-16 Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein Wintjens, René Bifani, Amanda Makha Bifani, Pablo NPJ Vaccines Article The SARS-CoV-2 outbreak originated in China in late 2019 and has since spread to pandemic proportions. Diagnostics, therapeutics and vaccines are urgently needed. We model the trimeric Spike protein, including flexible loops and all N-glycosylation sites, in order to elucidate accessible epitopes for antibody-based diagnostics, therapeutics and vaccine development. Based on published experimental data, six homogeneous glycosylation patterns and two heterogeneous ones were used for the analysis. The glycan chains alter the accessible surface areas on the S-protein, impeding antibody-antigen recognition. In presence of glycan, epitopes on the S1 subunit, that notably contains the receptor binding domain, remain mostly accessible to antibodies while those present on the S2 subunit are predominantly inaccessible. We identify 28 B-cell epitopes in the Spike structure and group them as non-affected by the glycan cloud versus those which are strongly masked by the glycan cloud, resulting in a list of favourable epitopes as targets for vaccine development, antibody-based therapy and diagnostics. Nature Publishing Group UK 2020-09-04 /pmc/articles/PMC7474083/ /pubmed/32944295 http://dx.doi.org/10.1038/s41541-020-00237-9 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wintjens, René Bifani, Amanda Makha Bifani, Pablo Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein |
title | Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein |
title_full | Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein |
title_fullStr | Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein |
title_full_unstemmed | Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein |
title_short | Impact of glycan cloud on the B-cell epitope prediction of SARS-CoV-2 Spike protein |
title_sort | impact of glycan cloud on the b-cell epitope prediction of sars-cov-2 spike protein |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7474083/ https://www.ncbi.nlm.nih.gov/pubmed/32944295 http://dx.doi.org/10.1038/s41541-020-00237-9 |
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