Objective:
Despite of antiviral drugs and successful treatment, an effective
vaccine against hepatitis C virus (HCV) infection is still required.
Recently, bioinformatic methods same as prediction algorithms, have
greatly contributed to the use of peptides in the design of immunogenic
vaccines. Therefore, finding more conserved sites on the surface
glycoproteins (E1 and E2) of HCV, as major targets to design an
effective vaccine against genetically different viruses in each genotype
was the goal of the study.
Materials and methods:
In this experimental study, 100 entire sequences of E1 and E2 were
retrieved from the NCBI website and analyzed in terms of mutations and
critical sites by Bioedit 7.7.9, MEGA X software. Furthermore, HCV-1a
samples were obtained from some infected people in Iran, and reverse
transcriptase-polymerase chain reaction (RTPCR) assay was optimized to
amplify their E1 and E2 genes. Moreover, all three-dimensional
structures of E1 and E2 downloaded from the PDB database were analyzed
by YASARA. In the next step, three interest areas of humoral immunity in
the E2 glycoprotein were evaluated. OSPREY3.0 protein design software
was performed to increase the affinity to neutralizing antibodies in
these areas.
Results:
We found the effective in silico binding affinity of residues in
three broadly neutralizing epitopes of E2 glycoprotein. First, positions
that have substitution capacity were detected in these epitopes.
Furthermore, residues that have high stability for substitution in these
situations were indicated. Then, the mutants with the strongest
affinity to neutralize antibodies were predicted. I414M, T416S, I422V,
I414M-T416S, and Q412N-I414M-T416S substitutions theoretically were
exhibited as mutants with the best affinity binding.
Conclusion:
Using an innovative filtration strategy, the residues of E2
epitopes which have the best in silico binding affinity to neutralizing
antibodies were exhibited and a distinct peptide library platform was
designed.