Plant polyphenols as context-dependent modulators of cellular signalling networks

Plant-derived polyphenols have attracted considerable attention because of their antioxidant, anti-inflammatory, and metabolic regulatory activities. However, despite extensive research, their biological actions are still frequently interpreted through simplified one-compound–one-pathway models, which inadequately explain their pleiotropic and context-dependent effects. Furthermore, existing studies and reviews often examine signalling pathways, structural characteristics, metabolism, and exposure biology separately, limiting a comprehensive understanding of how polyphenols regulate cellular networks. Therefore, this review aims to re-evaluate the mechanisms of representative polyphenols, including curcumin, quercetin, epigallocatechin-3-gallate (EGCG), and resveratrol, from a systems-level perspective and to examine how structural features influence signalling behaviour across different biological contexts. By integrating evidence from molecular studies, omics technologies, biotransformation research, microbiome-related metabolism, and translational investigations, we highlight that polyphenols function not as pathway-specific regulators but as context-dependent modulators of interconnected networks governing redox homeostasis, inflammation, autophagy, and energy metabolism. We further demonstrate that structural motifs such as electrophilic centres, catechol groups, gallate esters, and stilbene scaffolds influence signalling tendencies by affecting chemical reactivity, target accessibility, and metabolic fate without conferring pathway exclusivity. Based on these observations, we propose a conceptual framework of conditional signalling bias, in which polyphenol activity emerges from the dynamic interplay among chemical structure, metabolic transformation, target exposure, and network state. This framework provides a more realistic and mechanistically grounded interpretation of polyphenol action and offers a valuable foundation for future biomarker-guided, exposure-informed, and precision-oriented translational research in cardiometabolic, neurological, inflammatory, and oncological diseases.