Evidence map›Paper›PMID 40830226›Full record

ArticleScientific reports2025

Network pharmacology and experimental validation to elucidate the pharmacological mechanisms of Guben Xiezhuo decoction against renal fibrosis.

Shutao Chen, Yue Liu, Liwei Zhu, Jingyi Wu, Ziyun Xu, Yingyu Zhang, Minggang Wei, Zhenfang Du, Sheng Qiang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Shutao Chen *Department of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China.
Yue Liu *Department of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China.
Liwei ZhuDepartment of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China.
Jingyi WuDepartment of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China.
Ziyun XuDepartment of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China.
Yingyu ZhangDivision of Molecular Signaling, Department of the Advanced Biomedical Research, Interdisciplinary Graduate School of Medicine, University of Yamanashi, Chuo, 409-3898, Japan.
Minggang WeiTraditional Chinese Medicine Department, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China. weiminggang@suda.edu.cn.
Zhenfang DuDepartment of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China. zjgzy089@njucm.edu.cn.
Sheng QiangDepartment of Nephropathy, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, 215600, Jiangsu, China. zjgzy018@njucm.edu.cn.

Funding

2024 Suzhou Science and Education Driven Healthcare Enhancement Project MSXM2024006Jiangsu Province Leading Talents Cultivation Project for Traditional Chinese Medicine SLJ0330National Natural Science Foundation of China Grant No. 82405281Suzhou Applied Basic Research Technology Innovation Project SYWD2024050Suzhou Municipal Health Commission LCZX202332Suzhou Science and Technology Bureau SKY2023008Suzhou Science and Technology Development Plan Project SYW2024045Zhangjiagang Municipal Health Commission ZKYL2355Zhangjiagang Youth Science and Technology Innovation Project ZJGQNKJ202411
6 · The paper itself

Abstract

Guben Xiezhuo decoction (GBXZD), a traditional Chinese medicine (TCM), shows promise in treating chronic kidney disease (CKD) by reducing renal fibrosis (RF). This study seeks to uncover the exact mechanism behind GBXZD's therapeutic effects. This study identified 14 active components and 18 specific metabolites in the serum of GBXZD-treated rats via mass spectrometry. Potential target proteins were predicted using PubChem, TCMSP, and SwissTargetPrediction databases and refined through OMIM and Genecards databases. A total of 276 proteins were filtered from these potential target proteins to develop a protein-protein interaction (PPI) network to explore the interactions between GBXZD and RF target proteins, revealing significant correlations for proteins such as SRC, EGFR, and MAPK3. Subsequently, the active components and specific metabolites were employed for molecule docking simulation to assess their interactions with EGFR protein. The effects and mechanisms of GBXZD on RF were validated in a unilateral ureteral obstruction (UUO) rat model by assessing changes in RF-related protein expressions identified from the PPI network. GBXZD showed a reduction in the phosphorylation expression of SRC, EGFR, ERK1, JNK, and STAT3. In vitro, LPS stimulated HK 2 cells treated with the identified GBXZD bioactive components trans-3-Indoleacrylic acid and Cuminaldehyde exhibited significantly enhanced viability and reduced fibrotic marker expression and p-EGFR levels. KEGG pathway analysis suggested that GBXZD's anti-fibrotic effects might be mediated by inhibiting the EGFR tyrosine kinase inhibitor resistance and MAPK signaling pathways.

Indexed as

Drugs, Chinese HerbalKidneyKidney DiseasesNetwork PharmacologyAnimalsDisease Models, AnimalFibrosisHumansMaleMolecular Docking SimulationProtein Interaction MapsRatsRats, Sprague-DawleySignal TransductionDrugs, Chinese HerbalBioinformaticGuben Xiezhuo decoctionNetwork pharmacologyRenal fibrosis

Identifiers

PMID40830226
PMCPMC12365271

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.