A bioinformatic approach for novel Leishmania antigens

AUGUSTO BELLOMIO; MIGUEL FERNÁNDEZ DE ULLIVARRI; DIEGO J. MARCO

Trieste

Workshop; Workshop Molecular Biology of Leishmania; 2016

International Centre for Genetic Engineering and Biotechnology (ICGEB)

Leishmanisis comprises a group of parasitic diseases caused by the flagellated protozoan from genus Leishmania. Nowadays there are not effective vaccines or immunodiagnosis methods against these diseases, thus it is necessary the searching for new parasite antigens that are able to generate the adequate immune response. Bioinformatic programs for antigenic prediction are promising tools to ease this search. In this study we analyzed two L. braziliensis proteins (A and B) using epitope prediction algorithms for lymphocite B (LB), T (LB) and MHC from Immune Epitope Database (IEDB) BepiPred and IgPred. In an attempt to bioinformatically discriminate Th1 and Th2 responses, we analyzed a set of exclusive Th1- and Th2-deriving protein antigens from different organisms. From 36 direct and derived parameters available in the software, we selected 18 as statistically discriminative (ANOVA) between Th1 and Th2. Protein A and B were further analyzed and statistically compared to the Th1 and Th2 patterns. The study exhibited that A has similarity to Th1 pattern, pointing to a potential protective activity against L. braziliensis. Meanwhile, B fitted in a dual pattern Th1 and Th2, showing similarities to both of them. These data correspond to the empirical results observed for both proteins. Regarding these results, we conclude that epitope prediction software may be a very useful tool for the pre-selection of novel antigenic proteins against leishmaniasis and other diseases. Further validation of these methods could facilitate the empirical research for new vaccines and methods for diagnosis.