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Objective: To predict the molecular mechanism of Dihuang (Rehmanniae Radix) in the treatment of diabetic nephropathy (DN) complicated with depression based on network pharmacology. Methods: The components of Dihuang (Rehmanniae Radix) were identified from the Integrated Pharmacology-based Research Platform of Traditional Chinese Medicine (TCMIP), Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and relevant literature. The component targets were detected by combining the SwissTargetPrediction and PubChem databases. Disease targets were collected from the Therapeutic Target Database (TTD), DisGeNET, and Ensembl databases with “diabetic nephropathy” and “depression” as keywords. The disease-component targets were mapped using Venny 2.1.0 to obtain potential targets. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and Cytoscape 3.7.2. The co-expression genes of the key targets were collected based on the COXPRESdb 7.3. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for potential targets using R language. Target-component docking was verified and evaluated using Discovery Studio 4.5. Results: According to the databases and literature reports, Dihuang (Rehmanniae Radix) contained 65 active components, and had 155 related targets for the treatment of DN complicated with depression. PPI screening showed that the key targets included serine/threonine protein kinase 1 (AKT1), signal transducer and activator transcription 3 (STAT3), interleukin 6 (IL-6), mitogen-activated protein kinase 1 (MAPK1), and vascular endothelial growth factor A (VEGFA), etc. GO enrichment analysis mainly involved biological processes, such as lipid metabolism, protein secretion regulation, cell homeostasis, and phosphatidylinositol 3 kinase activity. KEGG pathway enrichment analysis included the role of the AGE-RAGE signaling pathway in diabetic complements, insulin resistance (IR), neurotrophin signal path, Toll-like receptor signaling pathway, relaxin signaling pathway, epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), etc. Molecular docking showed that the target had high affinity for stachyose, manninotriose, verbascose, nigerose, etc. Conclusion: Based on network parmacology, this study preliminarily predict the effects of Dihuang (Rehmanniae Radix) in treating DN complicated with depression by regulating inflammation, glucose metabolism, nution nerve, etc. |
