To analyze the ingredients in PG, ultraperformance liquid chromatography-quadrupole-time-of-flight tandem mass (UPLC-Q-TOF-MS/MS) technology was performed. Subsequently, using data mining and network pharmacology methodology, combined with Discovery Studio 2016 (DS), Cytoscape v3.7.1, and other software, active ingredients, drug-disease targets, and key pathways of PG in the treatment of CB were evaluated. Finally, the reliability of the core targets was evaluated using molecular docking technology and
A total of 36 compounds were identified in PG. According to the basic properties of the compounds, 10 major active ingredients, including platycodin D, were obtained. Based on the data mining approach, the Traditional Chinese Medicine Systems Pharmacology Database, and the Analysis Platform (TCMSP), GeneCards, and other databases were used to obtain targets related to the active ingredients of PG and CB. Network analysis was performed on 144 overlapping gene symbols, and twenty core targets, including interleukin-6 (IL-6) and tumor necrosis factor (TNF), which indicated that the potential signaling pathway that was most relevant to the treatment of CB was the IL-17 signaling pathway.
In this study, ingredient analysis, network pharmacology analysis, and experiment verification were combined, and revealed that PG can be used to treat CB by reducing inflammation. Our findings provide novel insight into the mechanism of action of Chinese medicine. Furthermore, our data are of value for the research and development of novel drugs and the application thereof.