Computational analysis develops a novel multiepitope vaccine for brucellosis, suggesting potential effectiveness in humans.
Background/Objectives: Brucella is a major global One Health threat, causing an estimated 2.1 million human infections and substantial livestock losses annually, with no vaccine currently available for humans, underscoring the urgent need for a safe and effective vaccine. Methods: Employing a reverse vaccinology approach, a novel 175-mer multiepitope vaccine (Mvax) targeting Brucella FrpB was computationally designed in this study, incorporating two B-cell, two MHC class I (MHC-I), and three MHC class II (MHC-II) epitopes selected for their high predicted antigenicity, safety, and IFN-γ-inducing potential. Human β-defensin-3 (hBD3) was fused to the N-terminus as an adjuvant, followed by comprehensive in silico evaluation of the construct. Results: Population coverage analysis predicted 99.59% global MHC class I/II coverage for selected epitopes. In silico analyses predicted that Mvax has high solubility (Protein-SOL score: 0.808), a high antigenicity score (VaxiJen: 1.06), and a negative GRAVY index (−0.881), indicating favorable predicted physicochemical characteristics. iMODS, CABS-Flex 3, and molecular dynamics simulations suggested theoretical stability trends for the modeled vaccine complexes. C-ImmSim immune simulations further predicted elevated Th1 cell populations and associated cytokines (IL-12, IFN-γ, IL-2) following both single and multiple simulated Mvax exposures. Conclusions: The computational analyses described here provide a theoretical modeling basis for an antivirulence multi-epitope vaccine design against human brucellosis, with predicted metrics and simulated immune responses requiring empirical validation.
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Mostafa F. N. Abushahba (2026) studied this question.
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