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Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19

An immunoinformatics-based approach was used to identify potential multivalent subunit CTL vaccine candidates for SARS-CoV-2. Criteria for computational screening included antigen processing, antigenicity, allergenicity, and toxicity. A total of 2604 epitopes were found to be strong binders to MHC c...

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Autores principales: Rencilin, Clayton Fernando, Rosy, Joseph Christina, Mohan, Manikandan, Coico, Richard, Sundar, Krishnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836868/
https://www.ncbi.nlm.nih.gov/pubmed/33422682
http://dx.doi.org/10.1016/j.meegid.2021.104712
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author Rencilin, Clayton Fernando
Rosy, Joseph Christina
Mohan, Manikandan
Coico, Richard
Sundar, Krishnan
author_facet Rencilin, Clayton Fernando
Rosy, Joseph Christina
Mohan, Manikandan
Coico, Richard
Sundar, Krishnan
author_sort Rencilin, Clayton Fernando
collection PubMed
description An immunoinformatics-based approach was used to identify potential multivalent subunit CTL vaccine candidates for SARS-CoV-2. Criteria for computational screening included antigen processing, antigenicity, allergenicity, and toxicity. A total of 2604 epitopes were found to be strong binders to MHC class I molecules when analyzed using IEDB tools. Further testing for antigen processing yielded 826 peptides of which 451 were 9-mers that were analyzed for potential antigenicity. Antigenic properties were predicted for 102 of the 451 peptides. Further assessment for potential allergenicity and toxicity narrowed the number of candidate CTL epitopes to 50 peptide sequences, 45 of which were present in all strains of SARS-CoV-2 that were tested. The predicted CTL epitopes were then tested to eliminate those with MHC class II binding potential, a property that could induce hyperinflammatory responses mediated by T(H)2 cells in immunized hosts. Eighteen of the 50 epitopes did not show class II binding potential. To our knowledge this is the first comprehensive analysis on the proteome of SARS-CoV-2 for prediction of CTL epitopes lacking binding properties that could stimulate unwanted T(H)2 responses. Future studies will be needed to assess these epitopes as multivalent subunit vaccine candidates which stimulate protective CTL responses against SARS-COV-2.
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spelling pubmed-78368682021-01-26 Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19 Rencilin, Clayton Fernando Rosy, Joseph Christina Mohan, Manikandan Coico, Richard Sundar, Krishnan Infect Genet Evol Research Paper An immunoinformatics-based approach was used to identify potential multivalent subunit CTL vaccine candidates for SARS-CoV-2. Criteria for computational screening included antigen processing, antigenicity, allergenicity, and toxicity. A total of 2604 epitopes were found to be strong binders to MHC class I molecules when analyzed using IEDB tools. Further testing for antigen processing yielded 826 peptides of which 451 were 9-mers that were analyzed for potential antigenicity. Antigenic properties were predicted for 102 of the 451 peptides. Further assessment for potential allergenicity and toxicity narrowed the number of candidate CTL epitopes to 50 peptide sequences, 45 of which were present in all strains of SARS-CoV-2 that were tested. The predicted CTL epitopes were then tested to eliminate those with MHC class II binding potential, a property that could induce hyperinflammatory responses mediated by T(H)2 cells in immunized hosts. Eighteen of the 50 epitopes did not show class II binding potential. To our knowledge this is the first comprehensive analysis on the proteome of SARS-CoV-2 for prediction of CTL epitopes lacking binding properties that could stimulate unwanted T(H)2 responses. Future studies will be needed to assess these epitopes as multivalent subunit vaccine candidates which stimulate protective CTL responses against SARS-COV-2. Elsevier B.V. 2021-04 2021-01-07 /pmc/articles/PMC7836868/ /pubmed/33422682 http://dx.doi.org/10.1016/j.meegid.2021.104712 Text en © 2021 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 Research Paper
Rencilin, Clayton Fernando
Rosy, Joseph Christina
Mohan, Manikandan
Coico, Richard
Sundar, Krishnan
Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19
title Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19
title_full Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19
title_fullStr Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19
title_full_unstemmed Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19
title_short Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19
title_sort identification of sars-cov-2 ctl epitopes for development of a multivalent subunit vaccine for covid-19
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836868/
https://www.ncbi.nlm.nih.gov/pubmed/33422682
http://dx.doi.org/10.1016/j.meegid.2021.104712
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