Computational vaccinology: an important strategy to discover new potential S. mansoni vaccine candidates

Abstract

The flatworm Schistosoma mansoni is a blood fluke parasite that causes schistosomiasis, a debilitating disease that occurs throughout the developing world. Current schistosomiasis control strategies are mainly based on chemotherapy, but many researchers believe that the best long-term strategy to control schistosomiasis is through immunization with an antischistosomiasis vaccine combined with drug treatment. Several papers on Schistosoma mansoni vaccine and drug development have been published in the past few years, representing an important field of study. The advent of technologies that allow large-scale studies of genes and proteins had a remarkable impact on the screening of new and potential vaccine candidates in schistosomiasis. In this postgenomic scenario, bioinformatic technologies have emerged as important tools to mine transcriptomic, genomic, and proteomic databases. These new perspectives are leading to a new round of rational vaccine development. Herein, we discuss different strategies to identify potential S. mansoni vaccine candidates using computational vaccinology.

Figure 1

Most common methodology for investigation of potential vaccine candidates. Possible targets are predicted based on sequences databases and proteomic analysis. Further bioinformatic studies provide detailed information about protein primary structure, topology, subcellular localization, conserved domains, HLA-peptide binding, and posttranslational modifications.* [–10].