Identification of a vaccine against schistosomiasis using bioinformatics and molecular modeling tools

Schistosomiasis is a serious public health problem in Brazil and worldwide. Although the drugs used to treatment schistosomiasis are effective, the disease continues to expand in all endemic countries due to constant reinfection, poor sanitation, and the lack of effective programs for disease control. However, advances generated through genome projects have provided important information that has improved the understanding of the biology of this parasite. These advances, associated with the advent of bioinformatic analysis, are becoming an important tool in reverse vaccinology. Through database access to the DNA and protein sequences of Schistosoma mansoni and the use of bioinformatics programs, fourteen epitopes were identified. Five epitopes were obtained from proteins whose immunogenic potential had already been assessed in other studies (KP), and nine whose immunogenic potential is unknown (UP). To improve stimulation of the host immune system, the selected epitopes were modeled with a sugar moiety. After this addition, all of the epitopes showed structures similar to those observed in the native proteins, but only eleven of the peptides presented thermodynamically stable structures. Prediction analysis and molecular modeling showed that the glycopeptides presented here are important targets in the search for a vaccine against schistosomiasis. Additionally, they suggest that these molecules may be used in immunological assays to evaluate the level of protection, the effect on pathology reduction and the profile of cytokines and antibodies induced by them.