The Molecular Mechanism of Radix Paeoniae Rubra.-Cortex Moutan. Herb Pair in the Treatment of Atherosclerosis: A Work Based on Network Pharmacology and In Vitro Experiments.
Caojian ZuoLidong CaiYa LiChencheng DingGuiying LiuChangmei ZhangHexiang WangYang ZhangMingyue JiPublished in: Cardiovascular toxicology (2024)
Radix Paeoniae Rubra. (Chishao, RPR) and Cortex Moutan. (Mudanpi, CM) are a pair of traditional Chinese medicines that play an important role in the treatment of atherosclerosis (AS). The main objective of this study was to identify potential synergetic function and underlying mechanisms of RPR-CM in the treatment of AS. The main active ingredients, targets of RPR-CM and AS-related genes were obtained from public databases. A Venn diagram was utilized to screen the common targets of RPR-CM in treating AS. The protein-protein interaction network was established based on STRING database. Biological functions and pathways of potential targets were analyzed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Cytoscape was used to construct the drug-compound-target-signal pathway network. Molecular docking was performed to verify the binding ability of the bioactive ingredients and the target proteins. The endothelial inflammation model was constructed with human umbilical vein endothelial cells stimulated with ox-LDL, and the function of RPR-CM in treating AS was verified by CCK-8 assay, enzyme-linked immunosorbent assay, and qPCR. In this study, 12 active components and 401 potential target genes of RPR-CM were identified, among which quercetin, kaempferol and baicalein were considered to be the main active components. A total of 1903 AS-related genes were identified through public databases and four GEO datasets (GSE57691, GSE72633, GSE6088 and GSE199819). There are 113 common target genes of RPR-CM in treating AS. PPI network analysis identified 17 genes in cluster 1 as the core targets. Bioinformatics analysis showed that RPR-CM in AS treatment was associated with multiple downstream biological processes and signal pathways. PTGS2, JUN, CASP3, TNF, IL1B, IL6, FOS, STAT1 were identified as the core targets of RPR-CM, and molecular docking showed that the main bioactive components of RPR-CM had good binding ability with the core targets. RPR-CM extract significantly inhibited the levels of inflammatory factors TNF-α, IL-6, IL-1β, MCP-1, VCAM-1 and ICAM-1 in HUVECs, and inhibited endothelial inflammation. This study revealed the active ingredients of RPR-CM, and identified the key downstream targets and signaling pathways in the treatment of AS, providing theoretical basis for the application of RPR-CM in prevention and treatment of AS.
Keyphrases
- molecular docking
- oxidative stress
- genome wide
- bioinformatics analysis
- cardiovascular disease
- healthcare
- type diabetes
- high throughput
- protein protein
- dna methylation
- small molecule
- wastewater treatment
- machine learning
- adverse drug
- smoking cessation
- risk assessment
- artificial intelligence
- copy number
- big data
- human health