Network pharmacology-based identification and experimental validation of active compounds from Qingda Granules against Ang II-induced hypertension

Background and objectives Hypertension is a significant global health issue that raises the risk of cardiovascular diseases (CVDs). Qingda Granule (QDG) is a traditional Chinese medicine formula used to treat hypertension, but its active compounds and mechanisms of action remain poorly understood. Methods Network pharmacology identified potential active compounds and KEGG pathways. Four compounds-gastrodin, rhynchophylline, baicalin, and liensinine were selected. Hypertension was induced in mice via Angiotensin II (Ang II) infusion. QDG (1145 mg/kg/day) or each compound (10 mg/kg/day) was administered orally once daily. Outcomes measured included systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), pulse wave velocity (PWV), and abdominal aortic wall thickness. Histological examination and immunohistochemistry for expression of total myosin light chain (MLC) and phosphorylation of myosin light chain (p-MLC) were performed in exploratory subgroups of three mice per group. Results Network pharmacology analysis identified 482 predicted targets overlapping with hypertension-related targets. The compound-target network was constructed and analyzed, and hub nodes were identified using multiple parameters, such as betweenness centrality and degree. These four selected compounds-gastrodin, rhynchophylline, baicalin, and liensinine-ranked among the top 50 nodes in the compound-target network. Consequently, these four compounds were selected for further validation. KEGG enrichment analysis identified vascular smooth muscle contraction as an enriched candidate pathway (18 targets). In vivo , QDG and all four compounds treatment significantly lowered blood pressure, lowered PWV, and reduced abdominal aortic wall thickness. Exploratory subgroup analyses showed attenuated aortic histopathological changes and reduced p-MLC immunoreactivity, with no significant difference in total MLC immunoreactivity in abdominal aortic tissues of Ang II-infused mice. Conclusion QDG and its four individually administered compounds attenuated blood pressure elevation and were associated with lower PWV and reduced abdominal aortic wall thickening in Ang II-infused mice, as well as reduced p-MLC immunoreactivity. These findings suggest that the QDG and its four compounds contribute to antihypertensive effects.

Authors

Institutions

Publication Details

Journal
Biochemistry and Biophysics Reports
Published
2026-11-07
DOI
https://doi.org/10.1016/j.bbrep.2026.102864
Primary Topic
Traditional Chinese Medicine Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Network pharmacology-based identification and experimental validation of active compounds from Qingda Granules against Ang II-induced hypertension

L Zhang, Aling Shen, 陈友琴, Zhi Guo et al.
2 links
Biochemistry and Biophysics Reports
Traditional Chinese Medicine Analysis
article

Network pharmacology-based identification and experimental validation of active compounds from Qingda Granules against Ang II-induced hypertension

L Zhang, Aling Shen, 陈友琴, Zhi Guo, Muhammad Mohsin, Farman Ali, Xiuli Zhang, Jun Peng, Guosheng Lin, Yaqiong Hu, Meizhu Wu
article en

Abstract

Background and objectives Hypertension is a significant global health issue that raises the risk of cardiovascular diseases (CVDs). Qingda Granule (QDG) is a traditional Chinese medicine formula used to treat hypertension, but its active compounds and mechanisms of action remain poorly understood. Methods Network pharmacology identified potential active compounds and KEGG pathways. Four compounds-gastrodin, rhynchophylline, baicalin, and liensinine were selected. Hypertension was induced in mice via Angiotensin II (Ang II) infusion. QDG (1145 mg/kg/day) or each compound (10 mg/kg/day) was administered orally once daily. Outcomes measured included systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), pulse wave velocity (PWV), and abdominal aortic wall thickness. Histological examination and immunohistochemistry for expression of total myosin light chain (MLC) and phosphorylation of myosin light chain (p-MLC) were performed in exploratory subgroups of three mice per group. Results Network pharmacology analysis identified 482 predicted targets overlapping with hypertension-related targets. The compound-target network was constructed and analyzed, and hub nodes were identified using multiple parameters, such as betweenness centrality and degree. These four selected compounds-gastrodin, rhynchophylline, baicalin, and liensinine-ranked among the top 50 nodes in the compound-target network. Consequently, these four compounds were selected for further validation. KEGG enrichment analysis identified vascular smooth muscle contraction as an enriched candidate pathway (18 targets). In vivo , QDG and all four compounds treatment significantly lowered blood pressure, lowered PWV, and reduced abdominal aortic wall thickness. Exploratory subgroup analyses showed attenuated aortic histopathological changes and reduced p-MLC immunoreactivity, with no significant difference in total MLC immunoreactivity in abdominal aortic tissues of Ang II-infused mice. Conclusion QDG and its four individually administered compounds attenuated blood pressure elevation and were associated with lower PWV and reduced abdominal aortic wall thickening in Ang II-infused mice, as well as reduced p-MLC immunoreactivity. These findings suggest that the QDG and its four compounds contribute to antihypertensive effects.

Biochemistry and Biophysics ReportsVol. 48
Fujian University of Traditional Chinese Medicine (CN), Rainbow Babies & Children's Hospital (US), Case Western Reserve University (US)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province
Good health and well-being
Openalex Percentile: Top 7%
Traditional Chinese Medicine Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon