Dental caries is a global public health problem, being the most common non-communicable disease. Streptococcus mutans, the causative agent of human cariogenic dental biofilms, produce glycosyltransferases (Gtfs) whose gene expression is modulated by the VicRK system, which makes them a promising target for dental biofilm inhibitor developments. Bioinformatics have playing a significant role in drug discovery programs mainly in novel hit identification. In this study, potential inhibitors against the S. mutans VicK system have been identified through Structure-based Virtual Screening performed between the VicK druggable sites followed byMolecular Dynamic simulations (MD) with binding affinity analysis by MM-PBSA approach. First, VicK protein was downloaded from PDB, and druggability analyses were performed by PockDrug and FTMap servers describing three interaction sites (S1, S2, and S3) that covered the most important domains for stability and activity. Next, a catechol virtual screening (n = 383) was performed on AutoDock4.2, and better-docked catechols showed strong binding affinity interaction through hydrogen bonding, hydrophobic interactions, and π-stacking with VicK auto kinase and phosphatase activity sites. Ligand efficiency indexes were also calculated (LE, LELP, LLE, and BEI) and showed optimal values. Furthermore, a 200 ns MD simulation run showed stability (RMSD and RMSF) and a high number of hydrogen bonds into peltatoside and maritimein, the two best VicK complexes. These results supported that catechols could potentially inhibit exopolysaccharides synthesis and be used in the biofilm management of new anti-cariogenic and antimicrobial agents.
Keywords: Caries; Streptococcus mutans; VicK; Virtual Screening; druggability analysis; glycosyltransferases.