In Silico Analysis of Neutralizing Antibody Epitopes on The Hepatitis C Virus Surface Glycoproteins

Document Type : Original Article

Authors

1 Department of Virology, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran

2 Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University-TMU, Tehran, Iran

3 Department of Biotechnology, Biotechnology Research Center, Venom and Biotherapeutics Molecules Lab, Pasteur Institute of Iran, Tehran, Iran

4 Department of Pharmacy, Drug Design and Development Research Center, Tehran University of Medical Sciences, Tehran, Iran

Abstract

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.

Keywords

References

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