TY - JOUR
T1 - Structure-guided discovery and validation of a potent RamR inhibitor targeting efflux-mediated multidrug resistance in Salmonella typhimurium
AU - Agrawal, Gopal Prasad
AU - Alam, Md Shamsher
AU - Alotaibi, Faisal
AU - Alqarni, Mohammad H.
AU - Foudah, Ahmed I.
AU - Alam, Aftab
AU - Al shehri, Zafer Saad
AU - Alkhoshaiban, Abdulaziz Saleh
AU - Alshehri, Faez Falah
N1 - Publisher Copyright:
© Institute of Microbiology, Academy of Sciences of the Czech Republic, v.v.i. 2025.
PY - 2025
Y1 - 2025
N2 - 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 (R2 = 0.975). Among the top-ranked compounds, 144095451 emerged as the most promising RamR inhibitor, as indicated by both computational predictions and ML modelling. Experimental verification with isothermal titration calorimetry (ITC) confirmed strong binding affinity (Ka = 5.43 × 10⁶ M⁻1; ΔH = –53.18 kcal/mol; stoichiometry n = 1.74) of 144095451. Antimicrobial profiling also established its efficacy, with a minimum inhibitory concentration (MIC) of 121.65 ± 0.5 µg/mL and a zone of inhibition of 18.54 ± 0.76. These results highlight compound 144095451 as a promising RamR-targeted antimicrobial lead. This research highlights the potential of the combinatorial approach, which utilizes computational screening, structural dynamics, machine learning-based biological activity prediction, and experimental confirmation of candidate molecules against multidrug-resistant S. typhimurium.
AB - 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 (R2 = 0.975). Among the top-ranked compounds, 144095451 emerged as the most promising RamR inhibitor, as indicated by both computational predictions and ML modelling. Experimental verification with isothermal titration calorimetry (ITC) confirmed strong binding affinity (Ka = 5.43 × 10⁶ M⁻1; ΔH = –53.18 kcal/mol; stoichiometry n = 1.74) of 144095451. Antimicrobial profiling also established its efficacy, with a minimum inhibitory concentration (MIC) of 121.65 ± 0.5 µg/mL and a zone of inhibition of 18.54 ± 0.76. These results highlight compound 144095451 as a promising RamR-targeted antimicrobial lead. This research highlights the potential of the combinatorial approach, which utilizes computational screening, structural dynamics, machine learning-based biological activity prediction, and experimental confirmation of candidate molecules against multidrug-resistant S. typhimurium.
KW - AcrAB-TolC efflux pump
KW - Multidrug-resistant
KW - RamR
KW - Salmonella typhimurium
UR - https://www.scopus.com/pages/publications/105019557766
U2 - 10.1007/s12223-025-01349-2
DO - 10.1007/s12223-025-01349-2
M3 - Article
AN - SCOPUS:105019557766
SN - 0015-5632
JO - Folia Microbiologica
JF - Folia Microbiologica
ER -