Design and Bioinformatic Evaluation of Multi-Epitope Protein to Diagnose Strongyloidiasis Infection

Background and purpose: Serological diagnosis of Strongyloides stercoralis (S. stercoralis) is often challenging due to cross-reactivity with other parasitic nematodes. Therefore, it is imperative to introduce new high-performance serological tests to flawlessly diagnose this neglected parasitic infection that enters through the digestive system and can even affect infertility. The purpose of the present study was to design a multi-epitope structure for the detection of S. stercoralis. Materials and methods: The present study is a computational immunoinformatics study. To this end, the highly antigenic parts and potential immunodominant epitopes of S. stercoralis were identified from the two antigenic proteins first and then all the selected parts were connected by a suitable linker. Next, the physicochemical characteristics of the designed structure were analyzed. Finally, tertiary structures were built and evaluated to determine the best ones. Results: Bioinformatics evaluation indicated that the designed protein structure can be hydrophilic, heat stable and acidic. In addition, the 3D model made was similar to the structure of natural proteins. Conclusion: Based on the findings of the study, the designed structure can be used as an efficient antigen in the ELISA system for the serological diagnosis of human strongyloidiasis