Computational approach for selection of epitope - based dengue vaccine targets

Abstract

High antigenic variability in the envelope protein of Dengue virus (DENV) has been the major problem in designing vaccines that can effectively combat different virus strains. In this study, a computational approach was adopted to identify and analyze evolutionary highly conserved amino acid sequences of the DENV envelope protein, with a focus on sequences of 9 amino acids or more, and thus immune-relevant as T-cell determinants. Different bioinformatics tools were used for revealing conserved regions in the dengue virus envelope protein and constructing the phylogenetic tree from the sequence database. The tools also rendered the prediction of immunogenicity to the proposed “in silico” vaccine targets. 2 peptide regions of at least 9 amino acids were highly conserved and identical in more than 95% of all collected DENV sequences. Both of them was found to be immune-relevant by their correspondence to known or putative HLA-restricted T cell determinants. The conservation of these sequences through the entire analysis of this study supports their potential as candidates for further wet laboratory experiments. Keywords: Dengue; Envelope protein; T-cell epitopes; Bioinformatics; Conserved regions; HLA.