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AuthorMathew, S.
AuthorMathew, Shilu
AuthorFakhroo, Aisha D.
AuthorSmatti, Maria
AuthorAl Thani, Asmaa A.
AuthorYassine, Hadi M.
Available date2022-09-13T14:49:40Z
Publication Date2022-04-01
Publication NameImmunogenetics
Identifierhttp://dx.doi.org/10.1007/s00251-021-01250-5
CitationMathew, S., Fakhroo, A. D., Smatti, M., Al Thani, A. A., & Yassine, H. M. (2022). Immunoinformatics prediction of potential immunodominant epitopes from human coronaviruses and association with autoimmunity. Immunogenetics, 74(2), 213-229.‏
ISSN00937711
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85122920081&origin=inward
URIhttp://hdl.handle.net/10576/33923
AbstractCross-reactivity between different human coronaviruses (HCoVs) might contribute to COVID-19 outcomes. Here, we aimed to predict conserved peptides among different HCoVs that could elicit cross-reacting B cell and T cell responses. Three hundred fifty-one full-genome sequences of HCoVs, including SARS-CoV-2 (51), SARS-CoV-1 (50), MERS-CoV (50), and common cold species OC43 (50), NL63 (50), 229E (50), and HKU1 (50) were downloaded aligned using Geneious Prime 20.20. Identification of epitopes in the conserved regions of HCoVs was carried out using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. Further, we identified sequences that bind multiple common MHC and modeled the three-dimensional structures of the protein regions. The search yielded 73 linear and 35 discontinuous epitopes. A total of 16 B-cell and 19 T-cell epitopes were predicted through a comprehensive bioinformatic screening of conserved regions derived from HCoVs. The 16 potentially cross-reactive B-cell epitopes included 12 human proteins and four viral proteins among the linear epitopes. Likewise, we identified 19 potentially cross-reactive T-cell epitopes covering viral proteins. Interestingly, two conserved regions: LSFVSLAICFVIEQF (NSP2) and VVHSVNSLVSSMEVQSL (spike), contained several matches that were described epitopes for SARS-CoV. Most of the predicted B cells were buried within the SARS-CoV-2 protein regions’ functional domains, whereas T-cell stretched close to the functional domains. Additionally, most SARS-CoV-2 predicted peptides (80%) bound to different HLA types associated with autoimmune diseases. We identified a set of potential B cell and T cell epitopes derived from the HCoVs that could contribute to different diseases manifestation, including autoimmune disorders.
Languageen
PublisherSpringer Science and Business Media Deutschland GmbH
SubjectAuto-immune disease
B cell
Coronavirus
Cross-reactivity
Immunoinformatics
T cell
TitleImmunoinformatics prediction of potential immunodominant epitopes from human coronaviruses and association with autoimmunity
TypeArticle
Issue Number2
Volume Number74
dc.accessType Open Access


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