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Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens
The 2019 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak has caused a large number of deaths, with thousands of confirmed cases worldwide. The present study followed computational approaches to identify B- and T-cell epitopes for the spike (S) glycoprotein of SARS-CoV-2 b...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251353/ https://www.ncbi.nlm.nih.gov/pubmed/32473352 http://dx.doi.org/10.1016/j.meegid.2020.104382 |
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author | Vashi, Yoya Jagrit, Vipin Kumar, Sachin |
author_facet | Vashi, Yoya Jagrit, Vipin Kumar, Sachin |
author_sort | Vashi, Yoya |
collection | PubMed |
description | The 2019 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak has caused a large number of deaths, with thousands of confirmed cases worldwide. The present study followed computational approaches to identify B- and T-cell epitopes for the spike (S) glycoprotein of SARS-CoV-2 by its interactions with the human leukocyte antigen alleles. We identified 24 peptide stretches on the SARS-CoV-2 S protein that are well conserved among the reported strains. The S protein structure further validated the presence of predicted peptides on the surface, of which 20 are surface exposed and predicted to have reasonable epitope binding efficiency. The work could be useful for understanding the immunodominant regions in the surface protein of SARS-CoV-2 and could potentially help in designing some peptide-based diagnostics. Also, identified T-cell epitopes might be considered for incorporation in vaccine designs. |
format | Online Article Text |
id | pubmed-7251353 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72513532020-05-27 Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens Vashi, Yoya Jagrit, Vipin Kumar, Sachin Infect Genet Evol Article The 2019 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak has caused a large number of deaths, with thousands of confirmed cases worldwide. The present study followed computational approaches to identify B- and T-cell epitopes for the spike (S) glycoprotein of SARS-CoV-2 by its interactions with the human leukocyte antigen alleles. We identified 24 peptide stretches on the SARS-CoV-2 S protein that are well conserved among the reported strains. The S protein structure further validated the presence of predicted peptides on the surface, of which 20 are surface exposed and predicted to have reasonable epitope binding efficiency. The work could be useful for understanding the immunodominant regions in the surface protein of SARS-CoV-2 and could potentially help in designing some peptide-based diagnostics. Also, identified T-cell epitopes might be considered for incorporation in vaccine designs. Elsevier B.V. 2020-10 2020-05-27 /pmc/articles/PMC7251353/ /pubmed/32473352 http://dx.doi.org/10.1016/j.meegid.2020.104382 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Vashi, Yoya Jagrit, Vipin Kumar, Sachin Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens |
title | Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens |
title_full | Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens |
title_fullStr | Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens |
title_full_unstemmed | Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens |
title_short | Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens |
title_sort | understanding the b and t cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: a computational way to predict the immunogens |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251353/ https://www.ncbi.nlm.nih.gov/pubmed/32473352 http://dx.doi.org/10.1016/j.meegid.2020.104382 |
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