Exploring the material basis and potential mechanism of spleen-strengthening and damp-resolving prescriptions in the treatment of diabetes mellitus complicated with obesity based on data mining, UPLC-Q-TOF-MS/MS and network pharmacology.

Diabetes combined with obesity is a global public health problem, with insulin resistance and chronic low-grade inflammation as key mechanisms. TCM regards spleen deficiency and phlegm-dampness as its core pathogenesis. This study constructs a research paradigm integrating clinical RCT data mining, UPLC-Q-TOF-MS/MS experimental component identification and network pharmacology-based prediction.This study predicted the multi-component, multi-target and multi-pathway mechanisms of core spleen-strengthening and damp-resolving prescriptions for this comorbidity. High-frequency herbs were screened via data mining from RCTs; chemical components were experimentally identified by UPLC-Q-TOF-MS/MS; intersecting targets and pathways were predicted by network pharmacology and preliminarily verified by semi-flexible molecular docking and molecular dynamics simulation. A 7-herb core prescription and 30 active components (nobiletin, puerarin, etc.) were determined. 350 common targets and hub genes (AKT1, MTOR, MMP9, PTGS2) were screened, with PI3K-Akt, lipid-atherosclerosis and diabetic AGE-RAGE as main pathways. Molecular docking showed strong component-target binding, which was further validated by dynamics simulation. The prescription improves diabetes with obesity through synergistic networks, regulating glycolipid metabolism and inflammation via the above pathways, supporting its modern clinical application.