The network mechanism exploration of Radix Notoginseng for Parkinson’s disease through network pharmacology

Objective: To investigate the network mechanism of Radix Notoginseng for Parkinson’s disease based on network pharmacology. Methods: “Radix Notoginseng” and “Parkinson’s disease” were searched as keywords in the Genecards database, followed by the Venny intersection analysis. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) analysis were conducted through bioinformatic methods. Finally, a literature review was utilized to evaluate the role of core genes in Parkinson’s disease. Results: 17 gene targets of Radix Notoginseng and 8184 Parkinson’s disease-related genes were downloaded. Then, 14 intersected gene targets through Venny intersection analysis. The GO analysis revealed that Radix Notoginseng treatment for Parkinson’s disease primarily activated through biological processes (BP) like protein phosphorylation and peptidyl-serine phosphorylation, cellular components (CC) like macromolecular complex and extracellular space, molecular functions (MF) like identical protein binding and protease binding. Through KEGG analysis, several crucial pathways were discovered, mainly including Lipid and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, Human cytomegalovirus infection, Fluid shear stress, and atherosclerosis. Finally, a total of ten core genes were identified in the core network construction via the PPI analysis, which are MMP9, AKT1, TNF, NFE2L2, VEGFA, RHOA, CASP3, CDKN1A, EGFR, IL1B. We used these ten core genes for literature comparison using PubMed, and none of the core genes were reported in literature related to Radix Notoginseng for Parkinson’s disease. Conclusion: This study discovered the fundamental network mechanism underlying Radix Notoginseng’s efficacy in treating Parkinson’s disease, evaluating its innovative potential and translational applications. These findings can offer a scientific foundation and valuable insights for subsequent experimental validation.