Immunoinformatics Based Design and In Silico Prediction of a Multi-Epitope Cocktail Vaccine Against Visceral Leishmaniasis

Visceral leishmaniasis (VL) is a serious parasitic disease caused by Leishmania species, with Leishmania donovani being one of the major causative species. The absence of an effective licensed human vaccine and the limitations associated with existing treatment highlight the need for alternative approaches for vaccine development. In the present study, an immunoinformatics-based approach was used to design a multi-epitope cocktail vaccine candidate against L. donovani. The protein sequence associated with accession number CAJ1986469 was analysed for potential immune-responsive regions. B-cell and T-cell epitopes, including MHC class I and MHC class II-associated epitopes, were investigated using the Immune Epitope Database (IEDB). Candidate epitopes showing an antigenicity threshold above 0.5 were considered for further analysis, and 20 epitopes from each selected group were evaluated. Sequence comparison was performed using Clustal Omega, resulting in the selection of Sequence 29 and Sequence 30 for vaccine construct development. The selected sequences were subsequently combined with suitable linker/adjuvant components to generate the proposed peptide construct. Structural modelling and three-dimensional visualization were then performed to examine the predicted structure of the construct. To investigate its possible interaction with immune receptors, TLR2, TLR4 and TLR9 structures obtained from the Protein Data Bank (PDB IDs: 2OZ7, 2Z64 and 5ZLN) were selected. Molecular docking was performed using the HDOCK server to assess the potential interaction between the designed construct and the selected receptors. Overall, this study presents a computational framework integrating epitope prediction, sequence analysis, vaccine construct design, structural modelling and molecular docking for the preliminary development of a multi-epitope vaccine candidate against L. donovani.