Immunoinformatics-Aided Analysis of RSV Fusion and Attachment Glycoproteins to Design a Potent Multi-Epitope Vaccine

Abstract

Respiratory syncytial virus (RSV) usually causes respiratory tract infections of upper airways in infants and young children. Despite recent medical advances, no approved vaccine is available to control RSV infections. Therefore, we conducted an immunoinformatics study to design and evaluate a potential multi-epitope vaccine against RSV. Sequence-based analyses of the glycoproteins F and G revealed a total of eight CD8 T-cell and three CD4 T-cell epitopes after considering antigenicity, binding affinity and other parameters. Molecular docking analysis confirmed that these T-cell epitopes developed strong structural associations with HLA allele(s). By integrating these prioritized epitopes with linkers and a cholera toxin-derived adjuvant, a multi-epitope vaccine was designed. The developed vaccine was found to be stable, non-allergenic, flexible and antigenic. Molecular docking analysis revealed a striking mean HADDOCK score (−143.3) of top-ranked vaccine-TLR cluster and a Gibbs free energy change (ΔG) value of −11.3 kcal mol−1. As per computational immune simulation results, the vaccine generated a high titer of antibodies (especially IgM) and effector T-cells. Also, codon optimization and in silico cloning ensured the increased expression of vaccine in Escherichia coli. Altogether, we anticipate that the multi-epitope vaccine reported in this study will stimulate humoral and cellular responses against RSV infection, subject to follow-up experimental validation.

Keywords

• respiratory syncytial virus
• multi-epitope vaccine
• molecular modeling
• molecular dynamics
• vaccine candidate