Next-generation multi-epitope subunit vaccine design: A computational approach utilizing two stable proteins to combat Human Metapneumovirus (HMPV)

Human Metapneumovirus (HMPV) has become a major contributor to acute respiratory infections, particularly in young children, the elderly, and individuals with weakened immune systems. It leads to considerable hospitalizations, morbidity, and treatment costs. Given its clinical impact, the development of novel vaccines against HMPV is essential. This study focused on employing immunoinformatics techniques to produce a multi-epitope vaccine. Multi-epitope vaccines may provide broader protection than live attenuated vaccines by targeting multiple viral strains. Using the NCBI database, consensus sequences of two stable viral proteins, the fusion glycoprotein and matrix protein from two HMPV strains, were obtained. T-cell and B-cell epitopes were identified using the protein sequences, followed by assessments of their stability, antigenicity, and allergenicity. Three vaccine constructs were developed, among which V2 demonstrated high antigenicity (0.5801), non-allergenicity, and favorable solubility (0.551). The final construct incorporated adjuvants, immunogenic epitopes, and optimized linkers to enhance the immune response. The constructs were evaluated for physicochemical properties, 3D structure, and model refinement before molecular docking and dynamics simulations with MHC alleles and the TLR-4 receptor. Immunological simulation studies suggest that the vaccine candidate may elicit a specific immune response against HMPV. In silico cloning and codon optimization indicated that Escherichia coli could be a suitable host for expression. These computational findings support the potential of a multi-epitope subunit vaccine against HMPV. However, further in vitro and in vivo validation is essential.

• Publication year

  2025

• Venue

  Comput. Biol. Medicine

• Publication date

  2025-08-18

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1016/j.compbiomed.2025.110935PMID 40829349
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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