Exploring Interactions of Volatile Constituents From Polygonum multiflorum With Inflammation‐Related Targets via Dual‐Ligand Docking and MD Simulations

Polygonum multiflorum Thunb ., a plant rich in diverse bioactive constituents, has been widely used in East Asia in functional foods and medicine to ameliorate inflammatory disorders through its multi‐component activity. The effectiveness of these botanical extracts is thought to involve complex interactions among diverse constituents; however, the molecular basis of such interactions remains insufficiently understood. In this study, we explored the anti‐inflammatory properties of the ethanol extract of Polygonum multiflorum ( PME) through a combination of chemical profiling and computational analysis. PME was found to reduce the production of nitric oxide, inducible nitric oxide synthase, and interleukin‐6 in LPS‐stimulated RAW 264.7 macrophages. Using HS‐SPME‐GC‐MS in conjunction with network pharmacology, we identified 32 volatile constituents, among which five core compounds were predicted to be associated with three inflammation‐related targets: ESR1, FASN, and NR1H3. Dual‐ligand molecular docking and molecular dynamics simulations suggested that the sequence of ligand binding may influence the stability and interaction patterns of protein–ligand complexes, offering insights into possible mechanisms of synergy and antagonism mediated by key residues such as ARG394 in ESR1. Overall, these findings contribute to a better understanding of how binding order and structural context may shape constituent‐target interactions, providing a basis for the further development of multi‐component natural product strategies against inflammation. This study underscores the relevance of incorporating multi‐ligand dynamics into natural product research and presents an integrated experimental–computational framework to investigate the cooperative or competitive behaviors of functional food constituents, thereby supporting the rational design of optimized multi‐target formulations.