Evidence map›Paper›PMID 39623712›Full record

ArticleCurrent computer-aided drug design2025

Network Pharmacology and

Hui Jin, Huaiyu Ma, Jie Wu, Ruizhe Wu, Haoran Xu, Weixing Chen, Linghui Li, Jingqi Zeng, Fan Wang

Abstract read
In one paragraph

Article in Current computer-aided drug design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hui JinDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Huaiyu MaDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Jie WuDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Ruizhe WuDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Haoran XuDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Weixing ChenDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Linghui LiDepartment of Sports Medicine, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, 100102, China.
Jingqi ZengDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.
Fan WangDepartment of Orthopedics, the Second Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, 410005, China.

Funding

General Guidance Project of Hunan Province Health Commission D202304075958General Project of Traditional Chinese Medicine Administration of Hunan Province B2024079National Natural Science Foundation of China 81904230Natural Science Foundation of Hunan Province 2023JJ60484Research Student Innovation Project of Hunan University of Chinese Medicine 2023CX108Youth Project of Hunan Provincial Department of Education 23B0344
6 · The paper itself

Abstract

objectiveThe Qing'e Pill (QEP) is widely used to alleviate low back pain and sciatica caused by Intervertebral Disc Degeneration (IDD). However, its active components, key targets, and molecular mechanisms are not fully understood. The aim of this study is to elucidate the molecular mechanisms through which the QEP improves IDD using database mining techniques.

methodsActive components and candidate targets of the QEP were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and the Bioinformatics Analysis Tool for Molecular Mechanisms of Traditional Chinese Medicine. IDD-related targets were obtained from the GeneCards database, and liver- and kidney-specific genes were retrieved from the BioGPS database. The intersection of these candidate targets was analyzed to identify potential targets for the QEP in IDD. A protein-protein interaction network analysis was performed using STRING and Cytoscape 3.7.2 software. Core targets were further analyzed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking was used to assess the binding affinity of active components to candidate targets, and animal experiments were conducted for validation.

resultsWe identified 65 potentially active components of the QEP that corresponded to 1,093 candidate targets, 2,108 IDD-related targets, and 1,113 liver- and kidney-specific genes. Key components included quercetin, berberine, isorhamnetin, and emodin. The primary candidate targets were Wnt5A, CTNNB1, IL-1β, MAPK14, MMP9, and MMP3. The GO and KEGG analyses revealed the involvement of these targets in Wnt signaling, TNF signaling, Wnt receptor activation, Frizzled binding, and Wnt-protein interactions. Molecular docking showed strong binding between these components and their targets. Animal experiments demonstrated that the QEP treatment significantly reduced the expression of Wnt5A, CTNNB1, IL-1β, MAPK14, MMP9, and MMP3 at high, medium, and low doses compared with the model group.

conclusionThe QEP alleviated IDD by modulating the Wnt/MAPK/MMP signaling pathways and reducing the release and activation of key factors.

Indexed as

Drugs, Chinese HerbalIntervertebral Disc DegenerationNetwork PharmacologyAnimalsComputational BiologyHumansMaleMedicine, Chinese TraditionalMolecular Docking SimulationProtein Interaction MapsDrugs, Chinese HerbalIntervertebral disc degenerationin vivo experimentsmolecular dockingmolecular mechanismsnetwork pharmacology.Qing’e Pill

Identifiers

PMID39623712
PMCPMC12272066

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.