The molecular mechanism of "Dahuang-Shengjiang-Banxia decoction" in the treatment of diabetic kidney disease was verified based on network pharmacology and molecular docking

Heliyon. 2024 Jan 19;10(2):e24776. doi: 10.1016/j.heliyon.2024.e24776. eCollection 2024 Jan 30.


Background: Explore the molecular mechanism of Dahuang-Shengjiang-Banxia Decoction (DSBD) in the treatment of diabetic kidney disease (DKD), using network pharmacology and molecular docking technology.

Method: The effective ingredients and targets of the DSBD were taken from the TCMSP database, while the disease targets were obtained via GeneCards, OMIM, DrugBank, TTD, and DisGeNET. Cytoscape 3.9.1 was used to create a drug-ingredient-target network diagram. STRING databases are also used to analyze the Protein-Protein Interaction (PPI) network of intersecting targets. The core targets was obtained by the intersection of the differential genes screened from the intersection target and GEO, and the core targets was enriched by Gene ontology (GO), Kyoto gene and genome (KEGG), and Gene Set Enrichment Analysis (GSEA). CIBERSORTx was used for immunoinfiltration analysis, and then the core targets was analyzed by Nephroseq V5 and KIT for clinical correlation analysis and single-cell sequencing. Lastly, AutoDock Vina was used for molecular docking of both the core targets and the top active elements.

Results: A total of 177 DSBD and 2906 DKD targets were screened. Six core targets were identified by screening, which were IL1B, MMP9, EGF, VEGFA, HIF1A, and PTGS2. The top 6 active ingredients are 6-gingerol, baicalin, oleic acid, β-sitosterol, linolenic acid, and aloe emodin. The core targets has good docking activity with the active ingredient.

Conclusion: DSBD may exert its therapeutic effect on DKD through multicomponent, multipath, and multi-target analyses. It is possible that VEGFA is a key target in therapy, and that the VEGF/PI3K/AKT signaling pathway plays a key role in therapy.

Keywords: Dahuang-Shengjiang-Banxia decoction (DSBD); Diabetic kidney disease; Molecular docking; Network pharmacology.