Designing an HCV diagnostic kit for common genotypes of the virus in Iran based on conserved regions of core, NS3-protease, NS4A/B, and NS5A/B antigens: an in silico approach

Hepatitis C virus (HCV) is a life-threatening virus that causes liver infection. If it is not detected in an early phase, the virus can lead to severe liver damages, including hepatic fibrosis, liver cirrhosis, and hepatocellular carcinoma. Today, computational design of the HCV diagnostic kit is employed to increase the specificity and sensitivity of the ELISA (enzyme-linked immunosorbent assay) diagnosis method according to the specific genotypes of the virus in each geographical region as well as to reduce costs in developing and low-income countries. The aim of this study was to design a multi-epitope protein from common HCV genotypes in Iran (1a, 1b, and 3a). For this purpose, potential immunodominant epitopes and highly antigenic regions were identified for six antigenic proteins and all of the segments were joined using a proper linker. The physico-chemical characteristics of the designed multi-epitope protein were evaluated and tertiary structures of the construct were modeled. Then, the models were evaluated and the best one was determined. Finally, the sequence of the protein was reverse-translated and optimized for high expression inE. coliexpression host. The findings of the present study indicated that the designed construct could detect the common HCV genotypes in Iran with high sensitivity and specificity.

Automated summary

The aim of this study was to design a multi-epitope protein from common HCV genotypes in Iran in order to increase the specificity and sensitivity of the diagnosis. By identifying potential epitopes in antigenic proteins and linking the segments, a construct capable of detecting HCV genotypes was successfully designed.