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Updated: Feb 14, 2026

Author Spotlight: An Antimicrobial Fabric Using Nano-Herbal Encapsulation of Essential Oils
Published on: April 7, 2023
Rational Design and Virtual Screening of Antimicrobial Terpene-Based Leads from Marrubium vulgare Essential Oil:
Ahmed Bayoudh1, Nidhal Tarhouni1, Raoudha Sadraoui2
1Laboratory of Enzyme Engineering and Microbiology, Engineering National School of Sfax (ENIS), University of Sfax, P.O. Box 1173, Sfax 3038, Tunisia.
None:
Pseudomonas aeruginosa elastase LasB accelerates refrigerated food spoilage through proteolytic degradation of muscle and milk proteins. While Marrubium vulgare essential oil terpenes exhibit antimicrobial activity, their weak potency and nonspecificity limit direct food preservation applications. This computational study aimed to rationally redesign terpene scaffolds into predicted selective LasB inhibitors. A virtual library of 635 terpene-peptide-phosphinic acid hybrids (expanded to 3940 conformers) was evaluated using consensus molecular docking (Glide/Flare) against LasB (PDB: 3DBK) and three human off-target proteases. Top candidates underwent duplicate 150 ns molecular dynamics simulations with MM/GBSA binding free-energy calculations. Computational screening identified thymol-Leu-Trp-phosphinic acid as the lead candidate with predicted binding affinity of -12.12 kcal/mol, comparable to reference inhibitor phosphoramidon (-11.87 kcal/mol), and predicted selectivity index of +0.12 kcal/mol representing a 2.3 kcal/mol advantage over human proteases. Molecular dynamics simulations indicated exceptional stability (98.7% stable frames, 0.12 Å inter-replica RMSD) with consistent zinc coordination. Structure-activity analysis revealed phosphinic zinc-binding groups (+1.57 kcal/mol), Leu-Trp linkers (+2.47 kcal/mol), and phenolic scaffolds (+1.35 kcal/mol) as predicted optimal structural features. This in silico study provides a computational framework and prioritized candidate set for developing natural product-derived food preservatives. All findings represent computational predictions requiring experimental validation through enzymatic assays, food model studies, and toxicological evaluation.
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