A Computational Approach for Identification of Epitopes in Dengue Virus Envelope Protein: A Step Towards Designing a Universal Dengue Vaccine Targeting Endemic Regions

Abstract

A major problem in designing vaccine for the dengue virus has been the high antigenic variability in the envelope protein of different virus strains. In this study, a computational approach was adopted to identify a multi-epitope vaccine candidate against dengue virus that may be suitable for large populations in the dengue-endemic regions. Different bioinformatics tools were exploited that helped the identification of a conserved immunological hot-spot in the dengue envelope protein. The tools also rendered the prediction of immunogenicity and population coverage to the proposed 'in silico' vaccine candidate against dengue. A peptide region, spanning 19 amino acids, was identified in the envelope protein which found to be conserved in all four types of dengue viruses. Ten proteasomal cleavage sites were identified within the 19-mer conserved peptide sequence and a total of 8 overlapping putative cytotoxic T cell (CTL) epitopes were identified. The immunogenicity of these epitopes was evaluated in terms of their binding affinities to and dissociation half-time from respective human leukocyte antigen (HLA) molecules. The HLA allele frequencies were studied among populations in the dengue endemic regions and compared with respect to HLA restriction patterns of the overlapping epitopes. The cumulative population coverage for these epitopes as vaccine candidates was high ranging from approximately 80% to 92%. Structural analysis suggested that a 9-mer epitope fitted well into the peptide-binding groove of HLA-A*0201. In conclusion, the 19-mer epitope cluster was shown to have the potential for use as a vaccine candidate against dengue.