Designing a multi-epitope vaccine candidate against pandemic influenza a virus: an immunoinformatics and structural vaccinology approach.

Influenza A virus (IAV) remains a significant public health concern due to its annual epidemics and potential for global pandemics. Despite the availability of countermeasures such as vaccines and antiviral treatments, their effectiveness is often questioned due to the emergence of novel strains with antiviral resistance and the variable efficacy of influenza vaccines compared to other vaccines. Traditionally, influenza vaccination strategies have focused on matrix, neuraminidase, and nucleoproteins. In this study, considering the crucial roles of HA and RdRp (PA, PB1, and PB2) of Influenza A, a reverse vaccinology approach is put forth in designing a possible promising antigenic protein toward the development of vaccines against H1N1 viruses. With the development of immunoinformatics approach, one can design/construct potential candidates for vaccine formulation against IAV with the epitope segments identified based on B- and T-cell recognition linked via adjuvants like EAAAK, GPGPG, and AAY linkers. Computational assessments of physicochemical properties, antigenicity, immunogenicity, allergenicity, and toxicity predictions, conducted to evaluate the potential of designed vaccine construct, indicated high antigenicity and potential interactions with immune receptors. Molecular docking of the vaccine construct with human immune receptors (MHCI, MHCII, TLR4, TLR7, and TLR8) followed by molecular dynamics simulations demonstrated stable dynamics with strong binding affinity. The computational immune response modeling with multiple dosages suggested significant immune activation by this construct against IAV. In essence, these findings highlight the potential immune property of the vaccine construct, and put forth the need of thorough preclinical assessments in transforming this construct as a vaccine against the challenging IAV pathogens.