Computational design of an mRNA vaccine targeting antifungal-resistant Lomentospora prolificans.

Lomentospora prolificans is an emerging opportunistic pathogen that predominantly affects immunocompromised individuals, as well as healthy individuals, often leading to disseminated disease with high mortality rates. Effective treatment is challenging due to its high intrinsic resistance to antifungal agents. To address this, we employed subtractive proteomics and reverse vaccinology approaches to identify potential antigenic proteins for the design of an mRNA-based multi-epitope vaccine (MEV). Our study identified four antigenic proteins as promising vaccine targets. A vaccine construct was developed using a combination of twelve cytotoxic T lymphocyte (CTL), nine helper T lymphocyte (HTL), and five linear B lymphocyte (LBL) epitopes. These epitopes were connected using appropriate linkers (AAY, GPGPG, and KK) and adjuvants to enhance antigenicity and immunogenicity. The vaccine construct was rigorously evaluated for its physicochemical properties, demonstrating high antigenicity, non-toxicity, non-allergenicity, stability, and solubility. Molecular docking studies were conducted to validate the interactions between the vaccine construct and the human toll-like receptor (TLR4). Immune simulation studies further confirmed the vaccine's potential to elicit a robust immune response. Additionally, molecular dynamics (MD) simulations, principal component analysis (PCA), dynamic cross-correlation matrix (DCCM) analysis, and binding free energy calculations were performed to assess the stability and efficacy of the vaccine-receptor complex. Codon optimization and in-silico cloning were carried out to ensure efficient expression of the vaccine in Escherichia coli strain K12. The findings of this study suggest that the proposed vaccine construct holds significant promise as a novel mRNA-based therapeutic candidate against L. prolificans infections. Further experimental validation is recommended to advance this vaccine toward clinical application.