MHC Class II restricted epitope prediction, crypticity analysis and B cell epitope identification from the proteome of Leishmania donovani.

Leishmania donovani (L. donovani) causes one of the dreadful diseases called visceral leishmaniasis (VL) affecting millions people in India and some parts of Africa. Several efforts have been made, no effective vaccine is available to date. Immunoinformatics methods play a critical role in predicting potential vaccine candidates. The present study showed extensive analysis of L. donovani proteins for the identification of MHC class II restricted epitopes, cryptic epitopes and B cell epitopes which may help in providing a diverse immune response. A total of 130 epitopes from L. donovani were identified on the basis of their binding towards HLA alleles. These peptides were checked for their hydrophobicity, IFN-γ and IL-10 inducing potentials.A total of 24 peptides were selected for modelling and docking. Molecular dynamics (MD) simulation of the docked complexes with the HLA-DRB1*0101 allele suggests 3 epitopes have the best binding interactions throughout the 100 ns simulation. These epitopes can be considered as potential vaccine candidates and may need further experimental validation before practical application. We also made an attempt to identify cryptic epitopes which remain largely unexplored in the context of L. donovani vaccine design and diagnosis. Out of 24 peptides selected previously, IC50 values of 5 peptides were decreased after the modification with tyrosine residue. Further replacement identified 2-3 modified peptides showing better docking and lesser IC50 values than the original peptides, suggesting cryptic behaviour of the epitopes. Linear and conformation B cell epitopes were also predicted which may suggest importance of these residues for eliciting humoral response.