EventsThe 7th International Electronic Conference on Foods
Published
This submission belongs to the session D. Food Microbiology & Biotechnologies of the event The 7th International Electronic Conference on Foods
Published date
23 Oct, 2026
Academic Editor
author-avatarEfstathios Giaouris
Citation
Goran Slivšek, Sandra Mijač, Nives Matković, Marija Fabijanec, Ivan Dolanc, Marin Marinović, Iva Brusić, Nevija Brstilo, Marlena Brstilo-Čičković, Donatella Verbanac, Miran Čoklo, Ivo Crnolatac, In Silico Assessment of Thymol as a Natural Plant-derived Antibacterial Candidate against Pseudomonas aeruginosa, in Proceedings of The 7th International Electronic Conference on Foods, 28 October–30 October 2026, MDPI: Basel, Switzerland
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In Silico Assessment of Thymol as a Natural Plant-derived Antibacterial Candidate against Pseudomonas aeruginosa

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Nives Matković 7
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1. Ruđer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia
2. Faculty of Medicine, University of Zagreb, Šalata 3, 10000 Zagreb, Croatia
3. Faculty of Medicine, University of Rijeka, Ulica braće Branchetta 20, 51000 Rijeka, Croatia
4. Faculty of Pharmacy and Biochemistry, University of Zagreb, Ulica Ante Kovačića 1, 10000 Zagreb, Croatia
5. Rijeka University Hospital Centre, Krešimirova 42, 51000 Rijeka, Croatia
6. Institute for Anthropological Research, Gajeva ulica 32, 10000 Zagreb, Croatia
7. Faculty of Medicine, University of Split, Šoltanska ulica 2A, 21000 Split, Croatia
8. Faculty of Health Studies, University of Rijeka, Ulica Viktora cara Emina 5, 51000 Rijeka, Croatia
Abstract

Introduction: Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen of relevance to food microbiology, biofilm formation, and antibiotic resistance. The inclusion of carbapenem-resistant P. aeruginosa among high-priority pathogens in the 2024 World Health Organisation Bacterial Priority Pathogens List highlights the need for new antibacterial candidates. This study aims to evaluate thymol against P. aeruginosa using an integrated in silico bioinformatics and cheminformatics approach.

Methods: The in silico workflow first evaluated thymol for physicochemical properties, predicted pharmacokinetic characteristics, and drug-likeness using the Swiss Absorption, Distribution, Metabolism and Excretion web tool (SwissADME). Literature-relevant P. aeruginosa protein targets with resolved structures were selected from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), after which potential binding pockets were identified using the Computed Atlas of Surface Topography of Proteins (CASTp). Docking calculations were performed in triplicate using AutoDock Vina. Binding orientations and interaction patterns were then analysed using the Python Molecular Graphics System (PyMOL), University of California, San Francisco Chimera (UCSF Chimera), and BIOVIA Discovery Studio Visualiser.

Results: Thymol showed a favourable in silico profile, with predicted pharmacokinetic and drug-like properties consistent with Lipinski’s Rule of Five. Triplicate molecular docking indicated plausible interactions with the selected P. aeruginosa targets, supporting the prioritisation of thymol for further experimental investigation. These findings are consistent with existing in vitro evidence reporting antibacterial and anti-biofilm activity of thymol against P. aeruginosa, as well as the activity of thymol-rich essential oils against antibiotic-resistant P. aeruginosa isolates.

Conclusions: This study suggests plausible molecular interactions between thymol and selected P. aeruginosa targets. These findings should be validated experimentally, starting with in vitro antibacterial and antibiofilm assays that include antibiotic-resistant isolates, followed by mechanistic studies and in vivo assessments to evaluate safety and efficacy. 

Keywords
antibacterial agents
bioinformatics
cheminformatics
drug resistance
food microbiology
molecular docking
pharmacokinetics
phytochemicals
Pseudomonas aeruginosa
thymol
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