ObjectivesNetwork pharmacology and molecular docking were used to predict endogenous active metabolites with protective effects in diabetic kidney disease (DKD).MethodsWe utilized metabolomics to screen differentially expressed metabolites in kidney tissues of mice with type 2 DKD and predicted potential targets using relevant databases. The interaction network between endogenous active metabolites and target proteins was established by integrating differentially expressed metabolites and proteins associated with DKD identified through proteomics. Gene ontology (GO) and signaling pathway enrichment analysis were performed. The biological functions of the active candidate metabolites and their effects on downstream pathways were also verified.ResultsMetabolomics revealed 130 differentially expressed metabolites. Through co-expression network analysis coupled with the investigation of differentially expressed proteins in proteomics, 2-hydroxyphenylpropionylglycine (2-HPG) emerged as a key regulator of DKD. 2-HPG was found to modulate the progression of DKD by regulating the conformation and activity of synaptophysin 1 (SYNJ1), with a correlation coefficient of 0.974. In vivo experiments revealed that SYNJ1 expression was significantly downregulated in the Macroalbuminuria Group compared to the Control Group and negatively correlated with proteinuria (r = -0.7137), indicating its important role in DKD progression. Immunofluorescence demonstrated that treatment with 2-HPG restores the expression of the foot process marker protein Wilms tumor-1 (WT-1) in podocytes injured by high glucose levels. Western blot and polymerase chain reaction support the involvement of SYNJ1 in this process.ConclusionsThis study demonstrated the significance of the 2-HPG/SYNJ1 signaling axis in safeguarding the foot process of podocytes in DKD.