Binding predictions and molecular docking as a computational approach to identify human T CD4 epitopes from Leishmania proteins

Background : So far there are not licensed leishmania vaccines for humans so is necessary to develop a strategy that improve treatment options or that can prevent the onset of the disease. To eliminate intracellular Leishmania amastigotes inside macrophage, a cellular immune response of CD4+ Th1 profile is essential, therefore the identification of sequences that binds strong to HLA class II pockets are good candidates to induce a protective immune response against Leishmania spp. The aim of this study was to identify T CD4+ epitopes from immunogenic Leishmania proteins. Methods : First, three prediction tools were used as screening comparing the 15mer sequences along the complete protein sequence against 25 HLA-DR alleles employing NH, SMT, CPA, CPB, and CPC proteins. Second, molecular docking and finally immune response predictions was run for the selection of best candidates. Results : 6 peptides were identified as HLA-DR strong binders simultaneously from the three bioinformatic prediction tools NH69-83, SMT133-148, CPA39-54, CPA301-316, CPB42-57, and CPC37-52. Molecular docking showed that those sequences bind to HLA-DRβ*04:01 pocket however some peptides bonded in a reverse way. Finally, 4 of them induced pro-inflammatory cytokines, while the other 2 showed anti-inflammatory profile. Conclusion : This bioinformatic strategy allowed a sequential screening from 1 857 possible peptides to 4 promising candidates, raising the probability of these sequences being natural T CD4+ Leishmania spp . epitopes in humans. SMT133-148, NH69-83, CPA39-54 and CPA301-316 seems to be a good vaccine candidate to be tested in further in vitro assays.