Novel multi-epitope peptide vaccine design and validation using bioinformatics approach targeting MSP-1 protein of Knowlesi malaria

Context: Plasmodium knowlesi is an emerging zoonotic malaria species in Southeast Asia, challenging elimination efforts. Aims: To design a safe and immunogenic multi-epitope vaccine (MEV) targeting the merozoite surface protein-1 (MSP-1) of P. knowlesi using a comprehensive immunoinformatics approach. Methods: Conserved regions of the P. knowlesi MSP-1 sequence were retrieved and analyzed to predict helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), and B cell epitopes. Epitopes were selected based on predicted immunogenicity, solubility, and safety. Suitable linkers were used to fuse selected epitopes, adjuvants, and sequences into a multi-epitope vaccine (MEV) construct. Physicochemical properties, immunogenicity, allergenicity, and antigenicity of the MEV were assessed in silico. Molecular docking and molecular dynamics (MD) simulation were conducted to evaluate MEV binding affinity and stability with toll-like receptor 4 (TLR4). The immunogenic potential was further evaluated using the C-ImmSim server to simulate host immune responses. Results: The 219-amino acid MEV construct was predicted to be stable, soluble, non-toxic, and non-allergenic, with 98.89% global population coverage. Molecular docking and MD simulations confirmed a stable interaction with TLR4. Immune simulation revealed efficient antigen clearance, significant production of IgM and IgG1/IgG2 antibodies, expansion of plasma and memory B cells, and activation of CD4⁺ and CD8⁺ T cells. A Th1-skewed cytokine response was observed, marked by elevated IFN-γ, IL-2, and IL-12 levels. Conclusions: The in silico-designed MEV demonstrated favorable immunological, structural, and population coverage profiles, supporting its potential as a promising vaccine candidate against P. knowlesi malaria. Further experimental validation is needed.