Immunoinformatics Approach for the Prediction of Novel Peptide-based Epitope Vaccine Design Against Leishmania Donovani: a Computational Biology Approach

Abstract

INTRODUCTION: A devastating vector-borne parasitic disease that primarily affects tropical and subtropical areas is visceral leishmaniasis (VL). As a neglected tropical disease with rising drug resistance and no approved vaccine, VL falls into this category. Traditional vaccine production methods are frequently exceedingly time-consuming and difficult. Designing multi-epitope vaccines with anticipated immuno-dominant epitopes of various antigenic proteins is now easier thanks to advancements in bioinformatics and their use in immunology. In order to construct an in-silico chimeric vaccine, we have chosen four antigenic proteins from Leishmania donovani and determined their T-cell and B-cell epitopes. The different physicochemical properties of the vaccine have been investigated, and it is anticipated that the tertiary structure of the chimaera construct will facilitate docking investigations and molecular dynamics simulations. RESULT: The epitopes are connected with particular linkers to create the vaccine construct. The vaccine's expected tertiary structure has been confirmed to be accurate, and docking experiments have shown that the construct has a strong affinity for the TLR-4 receptor. An examination of population coverage reveals that vaccination can protect the vast majority of people on the planet. The vaccination raises a pro-inflammatory response that results in the multiplication of activated T and B cells, according to in-silico immunological simulation experiments. CONCLUSION: The bioinformatics data cited above provide evidence that the design may function as a potential vaccination. To verify vaccine potency, additional wet lab production of the vaccine and in vivo studies in animal models must be carried out.