Jul 2026· INTERNATIONAL JOURNAL OF APPLIED AND CLINICAL RESEARCH· 0 citations· 26 references
TL;DR
The designed HA-based multi-epitope vaccine demonstrated promising immunogenicity, safety, structural stability, and broad population coverage in silico, and its potential as a vaccine candidate against Influenza A (H1N1) is supported.
Abstract
Background: Influenza A (H1N1) remains a significant global health threat due to its high mutation rate and antigenic variability, which limit the long-term efficacy of conventional strain-specific vaccines. This study employed an immunoinformatics approach to design a broadly protective multi-epitope vaccine targeting the hemagglutinin (HA) protein.
Methods: The HA protein sequence was analyzed for physicochemical properties, antigenicity, and epitope prediction. Promising B-cell and T-cell epitopes were selected and assembled into a multi-epitope vaccine construct. Structural modeling, molecular docking with Toll-like receptor 3 (TLR3), molecular dynamics simulation, population coverage analysis, codon optimization, and in silico cloning were performed to evaluate the vaccine candidate.
Results: The HA protein exhibited favorable physicochemical characteristics and strong antigenicity. The final vaccine construct was predicted to be highly antigenic, non-allergenic, and non-toxic, with a global population coverage of 81.68%. Structural validation confirmed model quality, while docking and molecular dynamics analyses demonstrated stable interactions with TLR3, indicating its potential to induce robust immune responses. Codon optimization and in silico cloning suggested efficient expression in the host system.
Conclusion: The designed HA-based multi-epitope vaccine demonstrated promising immunogenicity, safety, structural stability, and broad population coverage in silico. These findings support its potential as a vaccine candidate against Influenza A (H1N1), warranting further experimental validation through in vitro and in vivo studies.
H9N2 avian influenza virus (AIV) continues to mutate, leading to immunosuppression and secondary infections in poultry. Traditional inactivated vaccines mainly induce humoral immunity and have limited cross-protection efficacy against various subtypes of virus strains. In this study, we targeted the HA2 and M1 proteins of H9N2 as antigens and used immunoinformatics methods to design a broad-spectrum multi-epitope vaccine (MEV) that can simultaneously activate humoral and cellular immunity. Firstly, through systematic evolutionary analysis and sequence comparison, highly conserved amino acid sequence regions were selected from HA2 and M1 proteins. B-cell epitopes were predicted in the HA2 conserved sequence, and cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes were predicted in the M1 conserved sequence. Three candidate vaccines containing different epitope combinations were constructed. After secondary structure and physicochemical property comparisons, HM1 was determined as the optimal scheme. HM1 contains three B cell epitopes, two CTL epitopes, and three HTL epitopes, and was connected to chicken β-defensin at the N-terminus as a molecular adjuvant; a dendritic cell-targeting peptide was added at the C-terminus. The HM1 tertiary structure optimized by GalaxyRefine met the standards of a reliable model. The molecular docking results indicated that HM1 can form stable binding with chicken TLR2, TLR4, MHC I, and MHC II molecules, with binding free energies of −7.1 kcal/mol and −6.1 kcal/mol, respectively, and can form multiple hydrogen bonds and salt bridges. Normal mode analyses revealed that the HM1–TLR complex exhibits favorable dynamic properties at the computational level. The immune simulation prediction results showed that after vaccination with HM1, specific antibodies can be induced, B cells, helper T cells, and cytotoxic T cells can be activated, and IFN-γ and IL-2 can be secreted. In summary, the HM1 designed based on the conserved regions of HA2 and M1 proteins has good physicochemical stability and immunogenicity, providing a theoretical basis for the development of broad-spectrum and highly effective H9N2 vaccines.
Jiashuang Ji, Yating Lin, Zijian Zhu et al.· Microorganisms· 0 citations
This study presents a structurally optimized and validated multiepitope vaccine candidate against the emerging Batai orthobunyavirus, identifying a promising vaccine candidate for further investigation; however, its immunogenicity, safety, and protective efficacy before further vaccine development can be considered.
M. A. Alwaili, N. Al‐Hoshani, Huda A Alqahtani et al.· Pharmaceuticals· 0 citations
The H5N1 avian influenza virus poses a significant threat to both animal and human health, with a high potential for triggering a global pandemic. This study outlines a step-by-step immunoinformatics-driven approach to design a multi-epitope vaccine against H5N1. Potential vaccine candidates were identified by analyzing the sequences of conserved H5N1 proteins, including Hemagglutinin, Neuraminidase, and Matrix protein 1 and 2. B-cell epitopes and T-cell peptides were predicted and then screened for toxicity and allergenicity. The final vaccine construct has been verified for structural stability and computer simulation has been used to evaluate its theoretical potential for eliciting a long-lasting immune response. This
In silico
approach leverages a suite of computational tools to accelerate vaccine design by prioritizing promising candidates for experimental validation.
Ankita Singh, Omer S. Alkhnbashi, Filippo Castiglione· Frontiers in Applied Mathema...· 0 citations
The proposed multi-epitope vaccine shows promising immunological and structural properties, supporting its potential against S. typhimurium, pending experimental validation.
Mohammed Naveez Valathoor, A. P. Rajan· Scientific Reports· 0 citations
