Designing a multi-epitope influenza vaccine: an immunoinformatics approach

Abstract

Abstract Influenza continues to be one of the top public health problems since it creates annual epidemics and can start a worldwide pandemic. The virus’s rapid evolution allows the virus to evade the host defense, and then seasonal vaccines need to be reformulated nearly annually. However, it takes almost half a year for the influenza vaccine to become accessible. This delay is especially concerning in the event of a pandemic breakout. By producing the vaccine through reverse vaccinology and phage display vaccines, this time can be reduced. In this study, epitopes of B lymphocytes, cytotoxic T lymphocytes, and helper T lymphocytes of HA, NA, NP, and M2 proteins from two strains of Influenza A were anticipated. We found two proper epitopes (ASFIYNGRL and LHLILWITDRLFFKC) in Influenza virus proteins for CTL and HTL cells, respectively. Optimal epitopes and linkers in silico were cloned into the N-terminal end of M13 protein III (pIII) to create a multi-epitope-pIII construct, i.e., phage display vaccine. Also, prediction of tertiary structure, molecular docking, molecular dynamics simulation, and immune simulation were performed and showed that the designed multi-epitope vaccine can bind to the receptors and stimulate the immune system response.

Keywords

• Influenza
• Multi-epitope
• Immunoinformatics
• Reverse vaccinology
• Phage display vaccine
• Molecular dynamics simulation