Computational and Experimental Testing of Natural Products Against Staphylococcus aureus

Antimicrobial drug resistance is a global concern driven by diverse bacterial mechanisms, many of which are exacerbated by human activities. Staphylococcus aureus resistant strains pose an immediate threat and a substantial health burden. Natural products (NPs), recognized for their structural diversity and antimicrobial properties, can inhibit enoyl-acyl carrier protein reductase (FabI), a rate-limiting enzyme of the type II fatty acid synthase (FAS-II) system, which is essential for the biosynthesis of fatty acids that form the bacterial lipid membrane. Herein, we present a general workflow that integrates structure- and ligand-based approaches, specifically, consensus molecular docking with predictions of machine learning models to prioritize NPs candidates for testing as FabI inhibitors of S. aureus . The overarching goal of the study was to ultimately identify bioactive molecules against S. aureus . Structural analysis of top-1000 NPs identified 472 scaffolds, with the predominant chemotypes corresponding to chalcones, flavanones, flavones, and phenylpropanoids. Experimental evaluation of selected compounds highlighted taxoquinone as a promising scaffold, exhibiting moderate activity against S. aureus strains tested (pMIC = 3.21). Structure similarity calculations further identified additional promising NPs within the analyzed LANaPDB and NatUV DB collections.