Immunoinformatics approach to designing a multi-epitope vaccine against Saint Louis Encephalitis Virus

Abstract

The Saint Louis Encephalitis Virus (SLEV) is one of the causes of a rare, inflammatory condition of the brain tissues known as encephalitis. Belonging to the Flaviviridae family, SLEV can cause severe, detrimental repercussions on the central nervous system, leaving it impaired permanently. This study aimed to design and propose a multi-epitope vaccine candidate for preventing SLEV associated nervous system disorders. In this study, we used in silico approaches to predict potent epitopes on the envelope protein of SLEV by using multiple immunoinformatics and bioinformatics databases. We selected a total of 13 epitopes from the target envelope protein of SLEV through assessing their potential of eliciting both innate and acquired immunity by T and B lymphocyte mediated responses. Since SLEV is an RNA virus, conservancy of the epitopes were taken into account and the selected epitopes were found to be 100% conserved. The final multi-epitope vaccine subunit exhibited an antigenic score of 0.6797. Molecular docking of the multi-epitope vaccine construct was done with Toll-like receptor 4 (TLR4) protein and the energy score for the best model was found to be −1092.3. Expression capacity of the multi-epitope vaccine construct was tested in pET-28a (+) plasmid vector of Escherichia coli (strain-K12). Although the computational assays used in this study returned defensible results, further validation of the proposed vaccine candidate is required through in vitro and in vivo experiments to comment on its circumstantial efficacy.

Keywords

• Encephalitis
• Multi-epitope vaccine
• Cellular immunity
• Humoral immunity
• Immunoinformatics