Immunoinformatics-aided design of a potential multi-epitope peptide vaccine against Leishmania infantum

Abstract

Visceral leishmaniasis (VL) or kala-azar, the most severe form of the disease, is endemic in more than eighty countries across the world. To date, there is no approved vaccine against VL in the market. Recent advances in reverse vaccinology could be promising approach in designing the efficient vaccine for VL treatment. In this study, an efficient multi-epitope vaccine against Leishmania infantum, the causative agent of VL, was designed using various computational vaccinology methods. Potential immunodominant epitopes were selected from four antigenic proteins, including histone H1, sterol 24-c-methyltransferase (SMT), Leishmania-specific hypothetical protein (LiHy), and Leishmania-specific antigenic protein (LSAP). To enhance vaccine immunogenicity, two resuscitation-promoting factor of Mycobacterium tuberculosis, RpfE and RpfB, were employed as adjuvants. All the aforesaid segments were joined using proper linkers. Homology modeling, followed by refinement and validation was performed to obtain a high-quality 3D structure of designed vaccine. Docking analyses and molecular dynamics (MD) studies indicated vaccine/TLR4 complex was in the stable form during simulation time. In sum, we expect our designed vaccine is able to induce humoral and cellular immune responses against L. infantum, and may be promising medication for VL, after in vitro and in vivo immunological assays.