An immunoinformatic approach to design a novel vaccine against the human respiratory syncytial virus (hRSV) by targeting M2-1 protein

Abstract

Background: Human respiratory syncytial virus (hRSV) is the leading cause of upper and lower respiratory infection in infants, adults and immunocompromised persons. The matrix protein, M2-1 of hRSV is a cofactor of viral RNA polymerase that plays a crucial role during replication. This programmed study was designed to scrutinize potential immunogens from the M2-1 protein characterized from four different continents.

Methods: Sequence data obtained from NCBI databases were analysed by using a series of web and software based bioinformatics tools to find out the best epitope against hRSV.

Results: The phylogenetic data revealed a homogenized clustering of M2-1 protein for the African, European, and Asian clades while proteins from North American collections found to have a significant evolutionary detachment compared to three other clusters. Using various web-based bioinformatics tools, the study identified four common B-cell epitopes present in all the M2-1 proteins from four different clusters with higher antigenicity and conservancy. Among the 17 M2-1 protein investigated for T-cell epitopes, “VLQNLDVGL” peptide from A2 super-type, and “QSACVAMSK” and “CLNGRRCHY” from A3 super-type showed the highest antigenicity at >0.80 conservancy cut-off value. After evaluation of all antigenic properties, only “CLNGRRCHY” peptide qualified as a potential vaccine candidate against hRSV. Molecular docking revealed strong and stable binding of the epitope to major histocompatibility complexes (MHC) molecules in terms of hydrogen bonding.

Conclusion: The designed epitope could be used as a possible vaccine candidate against hRSV.

Keywords: hRSV; M2-1 protein; phylogenetic cluster; BCL and CTL epitopes; molecular docking