Mechanistic insights into Mfd inhibition by pharmacophore-guided ligands using molecular and steered molecular dynamics simulations.

Abstract

Antimicrobial resistance remains difficult to control because many bacteria rely on DNA repair pathways that help them survive antibiotic stress. One of the key players in this response is the Mutation Frequency Decline protein (Mfd), a transcription repair coupling factor that supports mutagenesis and persistence. Targeting Mfd therefore represents a promising strategy to limit bacterial evolvability rather than directly inhibiting growth. In this study, we integrate pharmacological screening with microbial resistance mechanisms using a pharmacophore-guided computational framework to identify inhibitors of Mfd in ESKAPE pathogens. A pharmacophore model derived from the known Mfd inhibitor NM102 (Reference 2) was employed to screen structurally diverse compounds from the PubChem database along with food-derived phytochemicals. Two lead candidates emerged from this analysis: Compound 1 (Carpaine), a natural alkaloid from Carica papaya, and a synthetic benzimidazole derivative Compound 2 (PubChem ID: 133869329). Both compounds showed more favorable predicted docking scores toward the ATP-binding region of Mfd compared to ATP (Reference 1) and NM102 (Reference 2). Molecular docking revealed conserved interactions within key functional motifs, while molecular dynamics simulations confirmed stable ligand-protein complexes. Binding free-energy calculations further supported favorable energetics, and steered molecular dynamics revealed higher peak rupture forces, particularly for Compound 1, indicating stronger mechanical resistance to ligand dissociation. Importantly, although Carica papaya extracts have previously been reported to enhance antibiotic efficacy in combination studies, the molecular basis of this effect and the specific contribution of Compound 1 remain unclear. The present work provides computational evidence supporting a proposed mechanism linking this effect to inhibition of Mfd-mediated DNA repair. Overall, this study highlights Mfd as an anti-evolvability target and demonstrates how pharmacophore-guided computational approaches can provide a computational framework for identifying potential ATP-competitive Mfd inhibitors against antimicrobial resistance, offering a data-driven direction for future antimicrobial strategies.