Prediction of CD8+ Epitopes in Leishmania braziliensis Proteins Using EPIBOT: In Silico Search and In Vivo Validation
Angelo Duarte,
Artur T L Queiroz,
Rafael Tosta,
Augusto M Carvalho,
Carlos Henrique Barbosa,
Maria Bellio,
Camila I de Oliveira and
Manoel Barral-Netto
PLOS ONE, 2015, vol. 10, issue 4, 1-10
Abstract:
Background: Leishmaniasis is caused by intracellular Leishmania parasites that induce a T-cell mediated response associated with recognition of CD4+ and CD8+ T cell Line 1Lineepitopes. Identification of CD8+ antigenic determinants is crucial for vaccine and therapy development. Herein, we developed an open-source software dedicated to search and compile data obtained from currently available on line prediction algorithms. Methodology/Principal Findings: We developed a two-phase algorithm and implemented in an open source software called EPIBOT, that consolidates the results obtained with single prediction algorithms, generating a final output in which epitopes are ranked. EPIBOT was initially trained using a set of 831 known epitopes from 397 proteins from IEDB. We then screened 63 Leishmania braziliensis vaccine candidates with the EPIBOT trained tool to search for CD8+ T cell epitopes. A proof-of-concept experiment was conducted with the top eight CD8+ epitopes, elected by EPIBOT. To do this, the elected peptides were synthesized and validated for their in vivo cytotoxicity. Among the tested epitopes, three were able to induce lysis of pulsed-target cells. Conclusion: Our results show that EPIBOT can successfully search across existing prediction tools, generating a compiled list of candidate CD8+ epitopes. This software is fast and a simple search engine that can be customized to search over different MHC alleles or HLA haplotypes.
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0124786
DOI: 10.1371/journal.pone.0124786
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