Unveiling the toxicity secrets of eugenol-like compounds: from interaction mechanisms to treatment strategies

Eugenol, isoeugenol, and methyleugenol are among the most widely used natural phenolic compounds in food, pharmaceuticals, and cosmetics. This study aims to comprehensively evaluate the toxicity and underlying mechanisms of eugenol-like compounds through integrating network toxicology, computational modeling, in vitro experiments, and disease bioinformatics. First, we established their association with liver diseases using toxicity prediction databases and published literature. Next, we anchored their core targets for inducing liver injury and liver Cancer, particularly the top five targets-EGFR, Src, HSP90AA1, TNF, and ESR1-through various compound, disease, and protein-protein interaction databases, alongside Cytoscape software. Molecular docking and dynamics simulation, combined with surface plasmon resonance experiments, confirmed stable binding of these compounds to core proteins. Functional enrichment analyses revealed significant enrichment of these targets in cancer-related pathways, signal transduction, viral infectious diseases, endocrine and metabolic diseases, and immune systems. Notably, chemical carcinogenesis-receptor activation and the IL-17 signaling pathway emerged as key Cancer and immune-related pathways influencing liver diseases. Using multi-omics databases and R software, we validated the prognostic significance of these core targets in liver Cancer patients. Based on three independent prognostic markers (CHEK1, CYP2C9, and HSP90AA1), we developed a novel risk-scoring system with robust predictive efficacy and demonstrated their correlation with tumor microenvironment infiltration, particularly Th2 and Th17 cell infiltration. These novel mechanistic insights and improved approaches enable more accurate safety assessments for eugenol-like compounds-based consumer products while informing innovative therapeutic strategies that combine multi-target and multi-pathway intervention with immunomodulation for liver disease management.

Computational modeling; Eugenol-like compounds; Liver cancer; Liver injury; Network toxicology; Surface plasmon resonance experiment.