Identification and analysis of epitope-based malarial vaccine targets using computational biology

Abstract

Malaria is a vector-borne infectious disease caused by protozoan parasite of the genus Plasmodium. The malaria vaccine which has been studied is designed to induce immunity to the sporozoite and to kill sporozoite-infected liver cells. A combination of bioinformatics approach and computational tools are used to screen and select antigen sequences as potential T-cell epitopes of supertype human leukocyte antigens (HLAs) alleles. This includes identification of epitopes from the transmembrane proteins sequences across Plasmodium genera. These epitopes have high target specificity with low mutational rate. A critical requirement of this strategy is the identification of stable peptide segments from the aligned multiple sequences of the transmembrane protein sequences. The stable peptide segments were identified by carrying out entropy analysis. Segments with low entropy values were extracted and made to interact with HLA molecules to generate better binding epitopes. Domains to which these epitopes belong were also identified.