Computational design of multi-epitope vaccine against Hepatitis C Virus infection using immunoinformatics techniques

Hepatitis C Virus (HCV) is a blood borne pathogen that affects around 200 million individuals worldwide. Immunizations against the Hepatitis C Virus are intended to enhance T-cell responses and have been identified as a crucial component of successful antiviral therapy. Nevertheless, attempts to mediate clinically relevant anti-HCV activity in people have mainly failed, despite the vaccines present satisfactory progress. In this study, we used an array of immunoinformatics approaches to design a multiepitope peptide-based vaccine against HCV by emphasizing 6 conserved epitopes from viral protein NS5B. The potential epitopes were examined for their possible antigenic combination with each other along with GPGPG linkers using structural modeling and epitope-epitope interaction analysis. An adjuvant (β-defensin) was introduced to the N-terminus to increase the immunogenicity of the vaccine construct. Molecular dynamics simulation discloses the most stable structure of the proposed vaccine. The designed vaccine is potentially antigenic in nature and can form stable and significant interaction with both receptors TLR2 and TLR3. The vaccine construct was also subjected to In-Silico cloning which confirmed its expression efficiency in a vector. The findings indicate that the designed multi-epitope vaccine have a great potential for preclinical and clinical research, which is an important step in addressing the problems related to HCV infection.