Computational design, structural modeling and immune evaluation of an amastin-based multi-epitope vaccine candidate against leishmaniasis.

Abstract

Leishmaniasis is a neglected tropical disease caused by protozoan parasites of the genus Leishmania. Currently, no licensed human vaccine is available and increasing drug resistance continues to compromise the disease control. The present study aimed to computationally design and evaluate a multi-epitope vaccine candidate targeting the conserved amastin protein of Leishmania donovani (UniProt ID: A5XDA6) using an integrated immunoinformatics approach. Cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell epitopes were predicted and sequentially prioritized on the basis of HLA-binding affinity, antigenicity, allergenicity and molecular docking with their respective HLA molecules. A total of twelve epitopes (five CTL, four HTL and three B cell epitopes) were selected. Conservancy analysis demonstrated that most epitopes were highly conserved across L.donovani, L. infantum and L. major, while population coverage analysis predicted 81.61% global coverage. The selected epitopes were assembled into a 209-amino acid vaccine construct using AAY, GPGPG and KK linkers with the TLR4 agonist RS-09 as an adjuvant. The construct was predicted to be antigenic, non-allergenic, stable and soluble whereas structural validation confirmed a high-quality three-dimensional model. Molecular docking demonstrated favourable interaction with the TLR4 receptor, while discontinuous B cell epitope analysis revealed structural similarity between the vaccine construct and the native amastin protein. Normal mode analysis, molecular dynamics simulation and immune simulation further supported the structural stability and immunogenic potential of the vaccine construct. A 100 ns molecular dynamics simulation confirmed the structural stability of the vaccine-TLR4 complex and MM/PBSA and MM/GBSA binding free energy analyses further supported favourable binding affinity between the vaccine construct and TLR4. Codon optimization and in silico cloning indicated favourable expression in the Escherichia coli pET-28a (+) expression system. These computational findings suggest that the proposed multi-epitope vaccine is a promising candidate which requires further experimental validation for realizing its potential as a vaccine against leishmaniasis.