Design of a Multi-epitope Antigen for Toxoplasmosis Diagnosis: An Immunoinformatics Approach

Abstract

Toxoplasma gondii, as an obligatory intracellular protozoan, can infect a diverse array of individuals and warm-blooded creatures. Considering the worldwide public health implications caused by T. gondii infection, it is an important goal to develop effective diagnostic tests or vaccines. The application of natural antigens derived from the parasite in these assessments encounters challenges, including the complexities of culturing the parasites, strain differences, and the high cost of kits produced based on natural antigens. The current bioinformatic study aimed to develop a multi-epitope T. gondii protein based on various immunoinformatic web servers to improve serodiagnosis. The linear and conformational B-cell epitope prediction of Surface Antigens 1(SAG1) and 2(SAG2), Dense granule proteins 2 (GRA2), 6 (GRA6), and 7 (GRA7), was conducted by the ABCpred and BepiPred servers, respectively. A variety of web servers were then accessed to predict antigenicity, solubility, and physicochemical properties, as well as to analyze secondary and tertiary structures, refine the 3D model, and validate the findings. Consequently, conformational B-cell epitopes were identified to explore potential protein-antibody interactions. In conclusion, further experimental evaluation is necessary for this multi-epitope construct for its subsequent incorporation in commercial serodiagnostic kits.