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

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dc.contributor.authorSaylor, Kyleen
dc.contributor.authorDonnan, Benen
dc.contributor.authorZhang, Chenmingen
dc.date.accessioned2022-08-30T14:23:58Zen
dc.date.available2022-08-30T14:23:58Zen
dc.date.issued2022en
dc.description.abstractThe 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.en
dc.description.notesFunding was provided by the American Association of Immunologists Careers in Immunology Fellowship Program (https://www.aai.org/Careers/Fellowships/CIFP) and the National Institute on Drug Abuse (U01DA036850, https://www.nih.gov/about-nih/what-we-do/nih-almanac/national-institute-drug-abuse-nida) to CZ. Funding was also provided by the Immune Epitope Database to KS for his attendance of the 2019 IEDB & nbsp;User Workshop. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
dc.description.sponsorshipAmerican Association of Immunologists Careers in Immunology Fellowship Program; National Institute on Drug Abuse [U01DA036850]; Immune Epitope Databaseen
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0265644en
dc.identifier.issn1932-6203en
dc.identifier.issue3en
dc.identifier.othere0265644en
dc.identifier.pmid35349604en
dc.identifier.urihttp://hdl.handle.net/10919/111668en
dc.identifier.volume17en
dc.language.isoenen
dc.publisherPLOSen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectheterozygote advantageen
dc.subjectnicotine vaccineen
dc.subjecthlaen
dc.subjectefficacyen
dc.subjectsafetyen
dc.subjectpredictionen
dc.subjectbindingen
dc.titleComputational mining of MHC class II epitopes for the development of universal immunogenic proteinsen
dc.title.serialPLoS Oneen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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