Dakpa Gyaltsen, Chiang Yu-Ting, Lin Li-Yin, Tsao Nai-Wen, Wang Chung-Hsuan, Pérez-Sánchez Horacio, Fernández Jorge Ricardo Alonso, Wang Sheng-Yang
Molecular and Biological Agricultural Sciences Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.
Graduate Institute of Biotechnology, National Chung-Hsing University, Taichung, Taiwan.
PLoS One. 2025 May 28;20(5):e0314125. doi: 10.1371/journal.pone.0314125. eCollection 2025.
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.
疲劳是一种与多种健康问题相关的普遍状况，然而确定用于管理疲劳的特定生物活性化合物仍然具有挑战性。本研究整合网络药理学和分子对接技术，通过靶向关键基因和分子途径来发现具有潜在抗疲劳特性的精油衍生化合物。使用PubChem对872种精油化合物进行了全面分析，并通过SwissTargetPrediction进行靶点预测。蛋白质-蛋白质相互作用（PPI）网络和KEGG通路分析确定了与疲劳相关的核心靶点，包括ALB、BCL2、EGFR、IL-6和STAT3，这些靶点与疲劳相关的代谢失调和炎症反应有关。分子对接显示，诸如桧烯、T-杜松醇和乙酸龙脑酯等关键化合物与核心靶点之间具有很强的结合亲和力，表明它们具有潜在的抗疲劳作用。然而，ADMET分析证实了T-杜松醇的类药性质，表明其具有良好的生物利用度和最小的毒性风险。因此，分子对接显示出高结合亲和力，通过100 ns的分子动力学模拟进一步验证，并证明了具有低均方根偏差（RMSD）的稳定相互作用。此外，氢键分析证实，T-杜松醇与EGFR中的Thr-790、ALB中的Arg-222和IL-6中的Arg-104等关键残基保持一致的相互作用，表明具有很强的结合稳定性。虽然本研究提供了有价值的计算见解，但仍需要进一步的体外和体内验证来证实这些发现并探索潜在的治疗应用。
