Explore Potential Molecular Mechanism of Gegen Qinliantang in Intervention of Atherosclerosis Based on Network Pharmacology and Molecular Docking
10.13422/j.cnki.syfjx.20220412
- VernacularTitle:基于网络药理学联合分子对接探究葛根芩连汤干预动脉粥样硬化的潜在分子机制
- Author:
Yi ZHENG
1
;
He GUO
1
;
Xi LUO
1
;
Yan-jie WANG
1
;
Dan-yu ZHAO
1
;
Xiao-fan FENG
1
;
Bao-kun LI
1
;
Jing-yu WANG
1
;
Lin ZHANG
1
;
Yu-xi LIU
1
;
Rui YU
1
;
Xian-sheng MENG
1
Author Information
1. Liaoning University of Traditional Chinese Medicine，Shneyang 110847，China
- Publication Type:Journal Article
- Keywords:
Gegen Qinliantang;
atherosclerosis;
network pharmacology;
molecular docking;
mechanism
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2022;28(11):51-59
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveThis study aims to explore the potential molecular mechanism of Gegen Qinliantang （GQL） in the intervention of atherosclerosis （AS） based on network pharmacology and molecular docking. MethodThe active components and targets of each medicinal in GQL were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， and AS-related genes from 7 databases. Thereby， the anti-AS targets of GQL were screened out. Cytoscape 3.8.0 was employed to construct the "component-target" network， and STRING the protein-protein interaction （PPI） network. Core targets were screened out with CytoNCA. R clusterProfiler was used for Gene Ontology （GO） term enrichment and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment of target genes， which were then visualized. Finally， molecular docking of the top ten active components with the core targets of AS was performed and the binding affinity was compared with that between atorvastatin and the core targets. ResultIn the end， 150 active components of GQL， 20 289 AS targets， and 213 common targets were retrieved， and 48 core common targets were screened out. They were mainly involved in the GO terms of nuclear receptor activity， ligand activation， and transcription factor activity and the pathways of fluid shear force and AS， advanced glycation end products-receptor for advanced glycation end products （AGE/RAGE）， interleukin-17 （IL-17）， tumor necrosis factor （TNF）， Toll-like receptor pathways and other signaling pathways closely related to AS. The molecular docking results showed that the effective components of GQL had high binding affinity to core targets of AS， and the binding affinity was even higher than that between the atorvastatin and core targets. The five groups with high binding affinity were puerarin-TNF， baicalein-inducible nitric oxide synthase 2 （NOS2）， puerarin-NOS2， and formononetin-NOS2， wogonin-NOS2. ConclusionThe above result provides new ideas for further exploration of this classical decoction.
