Chagas disease is one of the most important in America transmitted by Trypanosoma cruzi diseases with approximately 7 million people at risk,most of them from latin american. Due the non availability of an ideal drug or treatment , development of an effective, and affordable vaccine could be a solution for control and prevention o f this disease. In this study, use an bioinformatic approach to predict posibles epitopes of the candidates with help of MHC-II Binding Predictor from IEDB,using the prection method of recommended in IEDB and the set from Allele Class II from DbMHC and allelefrequencies.net with maximal population coverage, we analyze 10 sequence of surface protein expressed in trypanosoma cruzi in its three different stages present in the human body ,and keep the only ones with allotypes referring to the Latin American. A prediction of 70,000 epitopes per protein was obtained which were classified into three groups according to the shared epitopes, where the cruzipain belongs to a single group as it does not present similar epitopes with the other proteins. The first group contains the proteins Asp-3, Asp-2, Gp85, Gp90, Tc85, Sa85 with 17 shared epitopes and a population coverage of 87.89%. The second group Asp-3, Gp82, Gp83 with 31 shared epitopes and 87.89% population coverage. Because Cruzipain is not sharing any epitope, was selected the largest number of replicates contained in the same protein with a coverage above of 80 %.The selected epitopes are going to be synthesized to evaluate their potential as a possible vaccine against Trypanosoma cruzi.
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An approach to Trypanosoma cruzi Vaccine through the epitope prediction from proteins surface with IEDB
Published: 12 December 2016 by MDPI in MOL2NET'16, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 2nd ed. congress NICEXSM-02: North-Ibero-American Congress on Exp. and Simul. Methods, Valencia, Spain-Miami, USA, 2016
Keywords: Trypanosoma-cruzi Epitope Prediction Chagas disease