Structure-guided discovery and validation of a potent RamR inhibitor targeting efflux-mediated multidrug resistance in Salmonella typhimurium.

The emergence of multidrug-resistant (MDR) strains of Salmonella typhimurium (S. typhimurium) causes a significant global health challenge and underscores the need to develop potential antimicrobial agents. Here, we considered RamR, the major transcriptional repressor of the AcrAB-TolC efflux pump system, to identify promising inhibitors that can restore antibiotic susceptibility. We adopted an integrated computational-experimental research strategy that involved in silico screening of a structurally diverse compound database. The top four candidates (144095451, 17515455, 26648946, and 26648774) were selected for detailed analysis, which included re-docking, molecular dynamics (MD) simulations, binding free energy calculations, and free energy landscape analysis mapping. Density functional theory (DFT) was employed to explain the electronic properties and chemical reactivity of these molecules. To enhance the predictive accuracy of inhibitory potency (pIC₅₀), a machine learning (ML) regression model was developed, in which the ExtraTrees algorithm demonstrated high performance (R