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Structure-based identification of potential inhibitors of essential Staphylococcus aureus enzymes with in vitro antibacterial screening

Aug 2026 · Discover Chemistry · Vol 3 · 0 citations · 33 references

TL;DR

This study presents a structure-based screening workflow that identified potential inhibitory hits supported by in vitro antibacterial evaluation that may reduce the likelihood of resistance emergence by simultaneously disrupting multiple essential bacterial pathways.

Abstract

Staphylococcus aureus is a Gram-positive bacterium responsible for a wide range of clinical disorders. The emergence of multidrug-resistant strains continues to complicate the management of infections caused by this pathogen. Multiple-target-directed ligands (MTDLs) represent a polypharmacological drug discovery strategy that may reduce the likelihood of resistance emergence by simultaneously disrupting multiple essential bacterial pathways. In the present study, a structure-based in silico screening approach was employed to identify compounds with predicted interactions against five essential S. aureus enzymes, namely MurB, DNA gyrase B, dihydrofolate reductase, dihydropteroate synthase, and tyrosyl-tRNA synthetase. The identified multitarget hits were subjected to computational pharmacokinetic evaluation and molecular mechanics/generalized Born surface area calculations to estimate binding free energies. The selected compounds were subsequently evaluated through in vitro antibacterial assays, of which four candidates exhibited inhibitory activity against S. aureus, with two compounds demonstrating minimum inhibitory concentrations of 4 µg/mL against the reference strain. These two compounds also exhibited their most favorable computational binding profiles against MurB, with docking scores of − 8.884 and − 6.781 kcal/mol and MM/GBSA binding free energies of − 97.801 and − 72.404 kcal/mol. Accordingly, their MurB complexes were subjected to 100 ns molecular dynamics simulations, which showed stable protein–ligand complexes with RMSD values remaining below 3 Å throughout the simulation period. Overall, this study presents a structure-based screening workflow that identified potential inhibitory hits supported by in vitro antibacterial evaluation.

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