Immunoinformatics Design of a Multiepitope Vaccine (MEV) Targeting Streptococcus mutans: A Novel Computational Approach.

Abstract

Dental caries, a persistent oral health challenge primarily linked to Streptococcus mutans, extends its implications beyond dental decay, affecting over 4 billion individuals globally. Despite its historical association with childhood, dental caries often persists into adulthood with prevalence rates ranging from 60 to 90% in children and 26 to 85% in adults. Currently, there is a dearth of multiepitope vaccines (MEVs) specifically designed to combat S. mutans. To address this gap, we employed an immunoinformatics approach for MEV design, identifying five promising vaccine candidates (PBP2X, PBP2b, MurG, ATP-F, and AGPAT) based on antigenicity and conservation using several tools including CELLO v.2.5, Vaxign, v2.0, ANTIGENpro, and AllerTop v2.0 tools. Subsequent identification of linear B-cell and T-cell epitopes by SVMTrip and NetCTL/NetMHC II tools, respectively, guided the construction of a MEV comprising 10 Cytotoxic T Lymphocyte (CTL) epitopes, 5 Helper T Lymphocyte (HTL) epitopes, and 5 linear B-cell epitopes, interconnected by suitable linkers. The resultant MEV demonstrated high antigenicity, solubility, and structural stability. In silico immune simulations showcased the MEV's potential to elicit robust humoral and cell-mediated immune responses. Molecular docking studies revealed strong interactions between the MEV construct and Toll-Like Receptors (TLRs) and Major Histocompatibility Complex (MHC) molecules. Remarkably, the MEV-TLR-4 complexes exhibited a low energy score, high binding affinity, and a low dissociation constant. The Molecular Dynamic (MD) simulation analysis suggested that MEV-TLR-4 complexes had the highest stability and minimal conformational changes indicating equilibrium within 40 nanosecond time frames. Comprehensive computational analyses strongly support the potential of the proposed MEV to combat dental caries and associated infections. The study's computational assays yielded promising results, but further validation through in vitro and in vivo experiments is needed to assess its efficacy and safety.