Essential oil-derived compounds target core fatigue-related genes: A network pharmacology and molecular Docking approach
Year: 2025
Type: article
Abstract: Fatigue is a widespread condition associated with various health issues, yet identifying specific bioactive compounds for its management remains challenging. This study integrates network pharmacology and molecular docking to uncover essential oil-derived compounds with potential antifatigue properties by targeting key genes and molecular pathways. A comprehensive analysis of 872 essential oil compounds was conducted using PubChem, with target prediction via SwissTargetPrediction. The protein-protein interaction (PPI) network and KEGG pathway analysis identified core fatigue-related targets, including ALB, BCL2, EGFR, IL-6, and STAT3, in metabolic dysregulation and inflammatory responses linked to fatigue. Molecular docking exhibits strong binding affinity between key compounds such as Calamenene, T-cadinol, and Bornyl acetate and core targets, suggesting their potential antifatigue effects. However, ADMET analysis confirmed T-cadinol's drug-likeness, suggesting good bioavailability and minimal toxicity risks. Thus, molecular docking revealed high binding affinity, which was further validated through a 100 ns MD simulation and demonstrated stable interactions with low root mean square deviation (RMSD). Additionally, hydrogen bond analysis confirmed that T-cadinol maintained consistent interactions with key residues such as Thr-790 in EGFR, Arg-222 in ALB, and Arg-104 in IL-6, indicating strong binding stability. While this study provides valuable computational insights, further in vitro and in vivo validation is necessary to confirm these findings and explore potential therapeutic applications.
Source: PLoS ONE
Authors: Gyaltsen Dakpa, Yu-Ting Chiang, Li-Yin Lin, Nai-Wen Tsao, Chung-Hsuan Wang, Horacio Pérez-Sánchez, Jorge Ricardo Alonso Fernández, Sheng-Yang Wang
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,382
OpenAlex ID: W4410810537
