Designing and Modeling of Multi-epitope Proteins for Diagnosis of Toxocara canis Infection

Abstract

Serological investigation is the main method to achieve satisfactory results in Toxocara canis diagnosis. The accuracy of the native antigen used in the current diagnostic kits has proven to be insufficient as well as difficult to standardize. Therefore significant efforts have been made to find alternative reagents as capture antigens. Multi-epitope peptides are potential diagnostic markers to improve the accuracy of diagnostic kits. The main aim of this study is the prediction and design of a novel synthetic protein consisting of multiple immunodominant B cell epitopes by Use of three proteins TES-120, TES-30, and TES-26 of T. canis. Primary, secondary and tertiary structures of the proteins were analyzed by using several various online software (ExPasy, IEDB, ABCpred, SVMTriP). Then, B cell construct was assessed by machine learning and Physico-chemical approaches and finally, homology modeling of 3D structure of protein was evaluated. The results of in silico analyses indicated that regions with high immunogenicity for TES-120 protein are located at between residues 97–167, for TES-30 protein are in the residues 52–102, 172–207 and for TES-26 are in the residues 33–83, 130–180. These regions could have good potential features for designing the Multi-epitopes. Finally, selected epitopes were linked to each other by linkers. The average length of the constructs was 342 bp. Also, the high proportion of random coils and extended strands in construct suggest that the protein form antigenic epitopes. Expasy ProtParam classified the constructs with moderate stability and 56.2% residues of constructs were located in favored regions of the Ramachandran plot. In conclusion, immunoinformatics analysis indicated that this multi-epitope peptide can laid a theoretical basis to develop an appropriate diagnostic kit for human toxocariasis.