Abstract: Objective To study the therapeutic mechanism of Longqi Fang (LQF) for diabetic kidney disease (DKD) based on GEO database and network pharmacology. Methods LQF and DKD targets were obtained using the databases including GEO, TCMSP, CNKI, ChemDraw, and SwissTarget Prediction, and LQF-DKD intersection targets were obtained with VENNY. String was used for protein-protein interaction (PPI) analysis, and R package for KEGG and GO enrichment analysis. Cytoscape 3.7.2 software Network graphs were constructed. The results of network pharmacology analysis were verified in SD rat models of DKD by daily treatment of the rats with LQF at low (1 g/kg), medium (2 g/kg), and high (2 g/kg) doses, and kidney pathology was observed with HE staining and the changes in renal function were assessed. Western blotting was used to detect the expression levels of NF-κB and p-NF-κB proteins. Results We identified 760 main targets of LQF, and obtained 1026 differential genes using GEO database and 61 LQF-DKD intersection targets using Venny database. The core targets obtained through PPI network analysis included Myc, EGF, CASP3, VEGFA, CCL2, SPP1, VCAM1 and ICAM1. Go analysis showed that LQF affects mainly nuclear receptor activity and ligand activated transcription factor activity. KEGG analysis showed that LQF affects inflammatory signaling pathways by interfering with NF-κB, TNF, and PI3K-AKT. In rat models of DKD, treatment with LQF resulted in significant improvements of the renal functions (P<0.05) and glomerular and tubular structure and arrangement in a dose-dependent manner. Western blotting results showed that LQF dose-dependently downregulated NF-κB and p-NF-κB expressions in the rat models. Conclusion The therapeutic mechanism of LQF for DKD involves multiple components, targets and signal pathways that mediate an inhibitory effect on NF-κB signaling pathway to protect the renal function.

Key words: network pharmacology; Longqi Fang; diabetic kidney disease; animal experiments; nuclear factor-κB