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Computational mining of MHC class II epitopes for the development of universal immunogenic proteins

The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role i...

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Detalles Bibliográficos
Autores principales: Saylor, Kyle, Donnan, Ben, Zhang, Chenming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963548/
https://www.ncbi.nlm.nih.gov/pubmed/35349604
http://dx.doi.org/10.1371/journal.pone.0265644
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author Saylor, Kyle
Donnan, Ben
Zhang, Chenming
author_facet Saylor, Kyle
Donnan, Ben
Zhang, Chenming
author_sort Saylor, Kyle
collection PubMed
description The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts.
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spelling pubmed-89635482022-03-30 Computational mining of MHC class II epitopes for the development of universal immunogenic proteins Saylor, Kyle Donnan, Ben Zhang, Chenming PLoS One Research Article The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts. Public Library of Science 2022-03-29 /pmc/articles/PMC8963548/ /pubmed/35349604 http://dx.doi.org/10.1371/journal.pone.0265644 Text en © 2022 Saylor et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Saylor, Kyle
Donnan, Ben
Zhang, Chenming
Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
title Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
title_full Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
title_fullStr Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
title_full_unstemmed Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
title_short Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
title_sort computational mining of mhc class ii epitopes for the development of universal immunogenic proteins
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963548/
https://www.ncbi.nlm.nih.gov/pubmed/35349604
http://dx.doi.org/10.1371/journal.pone.0265644
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