An immunoinformatic approach driven by experimental proteomics: in silico design of a subunit candidate vaccine targeting secretory proteins of Leishmania donovani amastigotes

Abstract

Background: Visceral leishmaniasis (VL) caused by dimorphic Leishmania species is a parasitic fatal disease with high socio-economic burden in endemic areas worldwide. Sustaining control of VL in terms of proper and prevailing immunity development is a global necessity amid unavailability of a prophylactic vaccine. Screening of experimental proteome of human disease propagating form of L. donovani (amastigote) can be more pragmatic for in silico mining of novel vaccine candidates.Methods: By using an immunoinformatic approach, CD4+ and CD8+ T cell specific epitopes from experimentally reported L. donovani proteins having secretory potential and increased abundance in amastigotes were screened. A chimera linked with a toll-like receptor 4 (TLR4) peptide adjuvant was constructed and evaluated for physicochemical characteristics, binding interaction with TLR4 in simulated physiological condition and the trend of immune response following hypothetical immunization.Results: Selected epitopes from physiologically important L. donovani proteins were found mostly conserved in L. infantum-covering theoretically more than 98% of global population. The multiepitope chimeric vaccine was predicted as stable, antigenic and non-allergenic. Structural analysis of vaccine-TLR4 receptor docked complex and its molecular dynamics simulation suggest sufficiently stable binding interface along with prospect of non-canonical receptor activation. Simulation dynamics of immune response following hypothetical immunization indicate active and memory B as well as CD4+ T cell generation potential, and likely chance of a more Th1 polarized response. Conclusions:The methodological approach and results from this study could facilitate more informed screening and selection of candidate antigenic proteins for entry into vaccine production pipeline in future to control human VL.