Abstract
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 in E. coli expression 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.
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Abbreviations
- HCV:
-
Hepatitis C virus
- UTRs:
-
untranslated regions
- NTPase:
-
nucleoside triphosphatase
- RdRp:
-
RNA-dependent RNA protein
- Escherichia coli :
-
E. coli
- NCBI:
-
National Center for Biotechnology Information
- pI:
-
isoelectric point
- CAI:
-
codon adaptation index
- CFD:
-
codon frequency distribution
- ULR:
-
unreliable local regions
- ELISA:
-
enzyme-linked immunosorbent assay
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The authors wish to thank Shiraz University of Medical Sciences for supporting the conduction of this research.
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Mehrpour, K., Mirzaei, S.A., Savardashtaki, A. et al. 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. Biologia 76, 281–296 (2021). https://doi.org/10.2478/s11756-020-00566-z
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DOI: https://doi.org/10.2478/s11756-020-00566-z