Computational characterization of Plasmodium falciparum proteomic data for screening of potential vaccine candidates

Abstract

Advancement in the field of proteomics and bioinformatics offers tremendous opportunities for the development of novel epitope-based effective vaccine against human malaria. In this study, we have characterized 25 antigens as a vaccine candidate and screened the potential T-lymphocyte epitopes presented by human leukocyte antigen (HLA)-A, -B, and -DR molecules based on the proteomic data of Plasmodium falciparum. Of the 25 proteins, 22 were predicted as probable antigens and two were predicted as adhesions. In addition, seven proteins were predicted to contain signal peptide for secretary pathway and six proteins were found similar to the human and mouse reference proteins, whereas none of the proteins were predicted as allergen. A total of 14,841 peptides were predicted as epitope, presented by HLA class I and II supertypes that covered a broad human population (∼95%). Our results suggest that HLA-based multistage and multiepitope malaria vaccine would likely be needed to induce broader CD8 + as well as CD4 + T-cell responses. The predicted epitopes may be served as a useful diagnostic reagent for evaluating T-cell responses in the context of natural infection and/or vaccine trials.