Malaria, a life-threatening disease prevalent in tropical regions, primarily affects infants, children under five, pregnant women, travelers, and individuals with HIV/AIDS. This study utilized an immunoinformatics approach to design a peptide-based malaria vaccine targeting antigenic proteins, including Apical Membrane Antigen 1, Knob-Associated Histidine-Rich Protein, Merozoite Surface Protein 1, and Sporozoite Surface Protein 2. Antigenic protein sequences were screened for antigenicity, allergenicity, toxicity, and immune responses involving CTLs, B-cells, and HTLs. Selected epitopes were linked with appropriate linkers and an adjuvant to enhance immunogenicity, forming a vaccine construct. The construction, comprising 1473 amino acids, exhibited a molecular weight of 15.21 kDa, a theoretical pI of 8.94, an aliphatic index of 60.01, and an instability index of 31.66, indicating stability. It was hydrophilic (GRAVY: –0.385) with favorable half-lives in mammalian, yeast, and E. coli systems. Docking studies showed strong binding affinity to human TLR2 and TLR4. In silico cloning indicated a CAI value of 0.92 and a GC content of 59.31%. Further studies are needed to validate its efficacy and safety.

Background: Human metapneumovirus (HMPV) is a major cause of respiratory illness among vulnerable populations worldwide, yet no licensed vaccine or specific antiviral therapy is currently available. This study aimed to design novel multi-epitope mRNA vaccine candidates against HMPV using an immunoinformatics-based approach. Methods: Globally representative HMPV glycoprotein sequences were analyzed to predict cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-cell (LBL) epitopes. Selected epitopes were assembled into two multi-epitope mRNA vaccine constructs. The constructs were further evaluated for antigenicity, allergenicity, toxicity, and physicochemical properties using in silico tools. Structural stability and immune receptor interactions were assessed through molecular modeling and molecular docking analyses against Toll-like receptors 2 and 4 (TLR2 and TLR4). Results: Both vaccine constructs demonstrated high antigenicity, while remaining non-toxic and non-allergenic, with favorable physicochemical characteristics. Structural analyses indicated stable conformations of the vaccine models. Molecular docking studies revealed strong binding affinities with TLR2 and TLR4, suggesting their ability to effectively stimulate innate and adaptive immune responses. Conclusion: The two proposed multi-epitope mRNA vaccine constructs showed promising immunogenic, safety, and structural properties in silico, highlighting their potential as candidate vaccines against HMPV. These findings provide a strong foundation for further experimental validation and future vaccine development.

Rift Valley fever virus (RVFV) is a major zoonotic pathogen causing significant outbreaks in humans and livestock, with no licensed effective vaccines currently available. This study employed reverse vaccinology and immunoinformatics approaches to design three multi-epitope mRNA vaccine candidates against RVFV. Conserved antigenic regions from key viral proteins were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-cell (LBL) epitopes. The selected epitopes were assembled into three vaccine constructs incorporating appropriate linkers and the Human Beta Defensin 1 adjuvant. All three constructs were predicted to be highly antigenic (scores 0.5075–0.5467), non-allergenic, and non-toxic. They exhibited favorable physicochemical properties, high solubility, and excellent structural stability, with over 93% of residues in favored regions of the Ramachandran plot. Molecular docking demonstrated strong binding affinities with Toll-like receptors TLR-2 and TLR-3, while molecular dynamics simulations confirmed the stability of the vaccine-receptor complexes. Immune simulations predicted robust activation of both innate and adaptive immune responses, including significant B-cell and T-cell proliferation and cytokine production. Codon optimization yielded high Codon Adaptation Index (CAI) values (0.9–1.0) and optimal GC content (50.9–55.2%), indicating strong potential for efficient expression. These findings suggest that the designed multi-epitope mRNA vaccine constructs possess favourable predicted antigenic, physicochemical, structural and receptor-binding properties. However, all results are derived exclusively from computational analyses and should be interpreted as preliminary. The constructs require rigorous in vitro and in vivo validation to confirm antigen expression, immune activation, safety, immunogenicity and protective efficacy against RVFV before they can be considered viable vaccine candidates.