Anti-hypertensive effect and potential mechanism of gastrodia-uncaria granules based on network pharmacology and experimental validation.
Chu-Hao LiuQi-Qi XueYi-Qing ZhangDong-Yan ZhangYan LiPublished in: Journal of clinical hypertension (Greenwich, Conn.) (2024)
Hypertension has become a major contributor to the morbidity and mortality of cardiovascular diseases worldwide. Despite the evidence of the anti-hypertensive effect of gastrodia-uncaria granules (GUG) in hypertensive patients, little is known about its potential therapeutic targets as well as the underlying mechanism. GUG components were sourced from TCMSP and HERB, with bioactive ingredients screened. Hypertension-related targets were gathered from DisGeNET, OMIM, GeneCards, CTD, and GEO. The STRING database constructed a protein-protein interaction network, visualized by Cytoscape 3.7.1. Core targets were analyzed via GO and KEGG using R package ClusterProfiler. Molecular docking with AutodockVina 1.2.2 revealed favorable binding affinities. In vivo studies on hypertensive mice and rats validated network pharmacology findings. GUG yielded 228 active ingredients and 1190 targets, intersecting with 373 hypertension-related genes. PPI network analysis identified five core genes: AKT1, TNF-α, GAPDH, IL-6, and ALB. Top enriched GO terms and KEGG pathways associated with the anti-hypertensive properties of GUG were documented. Molecular docking indicated stable binding of core components to targets. In vivo study showed that GUG could improve vascular relaxation, alleviate vascular remodeling, and lower blood pressure in hypertensive animal models possibly through inhibiting inflammatory factors such as AKT1, mTOR, and CCND1. Integrated network pharmacology and in vivo experiment showed that GUG may exert anti-hypertensive effects by inhibiting inflammation response, which provides some clues for understanding the effect and mechanisms of GUG in the treatment of hypertension.
Keyphrases
- blood pressure
- hypertensive patients
- molecular docking
- network analysis
- heart rate
- protein protein
- signaling pathway
- molecular dynamics simulations
- cardiovascular disease
- blood glucose
- oxidative stress
- rheumatoid arthritis
- metabolic syndrome
- genome wide
- type diabetes
- single molecule
- combination therapy
- human health
- dna binding
- single cell
- case control
- glycemic control