Network Pharmacology and Validation of the Antidepressant Mechanisms of Qiangzhifang in a Chronic Restraint Stress-induced Depression Rat Model

Depression is a complex psychiatric disorder that poses significant treatment challenges.Qiangzhifang (QZF), a compound used in traditional Chinese medicine, demonstrates potential clinical efficacy in treating depression.However, the mechanisms of action and active ingredients of QZF have not been fully elucidated.The primary aim of this study was to elucidate the effective active ingredients and potential molecular mechanisms of QZF for the alleviation of depression by integrating network pharmacology predictions with experimental validations. We adopted a chronic restraint stress (CRS) rat model and conducted behavioral tests such as the open field test (OFT), sucrose preference test (SPT), and forced swimming test (FST) to evaluate the therapeutic effects of QZF on depression. Regarding behavioral parameters, the QZF group exhibited significantly higher body mass, sucrose preference ratio, and central zone residence time compared to the model group (P < 0.01, P < 0.01, P < 0.01), and a significantly reduced immobilization time in the forced swimming test (P < 0.001).Network pharmacology and molecular docking studies suggest that QZF may have antidepressant effects by modulating the HIF-1 and JAK-STAT pathways, with key target genes including AKT1, IL-6, MTOR, and TP53, implicated in inflammation, neuroprotection, and apoptosis.In conclusion, this study offers new insights into the modernization and development of Chinese medicine compounds for the comprehensive treatment of depression.

Authors

Institutions

Publication Details

Journal
Journal of Visualized Experiments
Published
2025-06-06
DOI
https://doi.org/10.3791/68198
Primary Topic
Tryptophan and brain disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Network Pharmacology and Validation of the Antidepressant Mechanisms of Qiangzhifang in a Chronic Restraint Stress-induced Depression Rat Model

Jian‐Lin Wu, Tongzheng Liu, Jie Liu, Wenjing Ren
Journal of Visualized Experiments
Tryptophan and brain disorders
article

Network Pharmacology and Validation of the Antidepressant Mechanisms of Qiangzhifang in a Chronic Restraint Stress-induced Depression Rat Model

Jian‐Lin Wu, Tongzheng Liu, Jie Liu, Wenjing Ren
article en

Abstract

Depression is a complex psychiatric disorder that poses significant treatment challenges.Qiangzhifang (QZF), a compound used in traditional Chinese medicine, demonstrates potential clinical efficacy in treating depression.However, the mechanisms of action and active ingredients of QZF have not been fully elucidated.The primary aim of this study was to elucidate the effective active ingredients and potential molecular mechanisms of QZF for the alleviation of depression by integrating network pharmacology predictions with experimental validations. We adopted a chronic restraint stress (CRS) rat model and conducted behavioral tests such as the open field test (OFT), sucrose preference test (SPT), and forced swimming test (FST) to evaluate the therapeutic effects of QZF on depression. Regarding behavioral parameters, the QZF group exhibited significantly higher body mass, sucrose preference ratio, and central zone residence time compared to the model group (P < 0.01, P < 0.01, P < 0.01), and a significantly reduced immobilization time in the forced swimming test (P < 0.001).Network pharmacology and molecular docking studies suggest that QZF may have antidepressant effects by modulating the HIF-1 and JAK-STAT pathways, with key target genes including AKT1, IL-6, MTOR, and TP53, implicated in inflammation, neuroprotection, and apoptosis.In conclusion, this study offers new insights into the modernization and development of Chinese medicine compounds for the comprehensive treatment of depression.

Journal of Visualized Experiments(220)
Shandong University of Traditional Chinese Medicine (CN)
Good health and well-being
Openalex Percentile: Top 87%
Tryptophan and brain disorders
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.