Machine Learning-Driven Discovery of STAT3 as a Pivotal Target for Wen-Wei-San-Ji Formula in Chronic Atrophic Gastritis Therapy: Multi-Omics Integration and Experimental Confirmation

The study investigated Wen-Wei-San-Ji (WWSJ), a Traditional Chinese Medicine formula for chronic atrophic gastritis (CAG), revealing its multi-component therapeutic mechanism. Through network pharmacology and machine learning approaches, researchers identified 53 bioactive compounds and 207 potential targets in WWSJ, with STAT3 inhibition emerging as a crucial pathway. Molecular docking analysis demonstrated strong binding affinity between WWSJ's active components and target proteins. Subsequent in vitro and in vivo experiments validated the formula's significant therapeutic effects against CAG. These findings provide scientific evidence supporting WWSJ's clinical application for CAG treatment through its multi-target regulatory action, bridging traditional use with modern pharmacological understanding. In conclusion, WWSJ may exert its effects on proteins involved in signaling pathways such as JAK-STAT by regulating the expression of STAT3 and p-STAT3(Tyr 705). Through a multi-component, multi-target, and multi-pathway approach, WWSJ collectively impacts the progression of CAG. The present exploration provides a theoretical basis for subsequent clinical research on WWSJ in the treatment of CAG.