Abstract: The chemical components of Angelica sinensis Radix- Cinnamomi cortex was identified, and the anti-inflammatory mechanism of the herb pair was predicted in combination with network pharmacology. GC-MS was used to analyze the volatile components of the herb pair, and then the potential targets of the active components were predicted through the TCMSP database and the Swiss Target Prediction database; inflammation-related gene targets were got through TTD database and GeneCards database; Cytoscape 3.7.2 software was used to construct a drugs-components-targets network diagram; string database and Cytoscape 3.7.2 software were adopted to build a target PPI network, then screening out key targets; the Clsuter Profiler program package in R 3.6.1 software was used to perform gene ontology （GO） function enrichment and KEGG pathway enrichment analysis for potential targets. The results showed that 35 kinds of volatile components were identified from the herb pair, accounting for 70.53% of the total volatile components. From the screening, 33 active compounds, 35 key targets, 1 296 biological processes, and 155 signal pathways were obtained. According to the prediction of network pharmacology results, the herb pair may regulate lipids and atherosclerosis, human cytomegalovirus infection, IL-17 and other signaling pathways through active ingredients such as β-caryophyllene, α-humulene, and α-pinene, and key targets such as TNF-, IL-6, and IL-1B, thereby synergistically exerting anti-inflammatory effects.

Key words: Angelica sinensis Radix, Cinnamomi cortex, inflammation, GC-MS（Gas Chromatography-Mass spectrometer）, network pharmacology