Evidence map›Paper›PMID 38243957›Full record

ArticleCombinatorial chemistry & high throughput screening2025

Network Pharmacology Analysis and

Jianxin Guo, Zhongbing Wu, Xiaoyue Chang, Ming Huang, Yu Wang, Renping Liu, Jing Li

Open access · hybridAbstract read
In one paragraph

Article in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Therapeutic Potential ofPharmaceuticals (Basel, Switzerland) · 2025
    Article
  3. Network Pharmacology and Validation of the Combinative Therapy ofCombinatorial chemistry & high throughput screening · 2025
    Article
  4. Article
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

7 authors at 1 institution in 1 country.

Jianxin GuoCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0009-0008-7599-4149
Zhongbing WuCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0000-0003-4006-0414
Xiaoyue ChangCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0000-0002-3697-6895
Ming HuangCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0009-0008-1737-0258
Yu WangCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0009-0007-8176-318X
Renping LiuCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0009-0008-4374-7207
Jing LiCollege of Integrated Chinese and Western Medicine, Hebei Medical University, Shijiazhuang 050011, China.ORCID 0000-0002-0592-2712
Hebei Medical University · CN

Funding

Hebei Medical University USIP2023150Hebei Province Traditional Chinese Medicine Scientific Research Subjects Programme 2024110National Natural Science Foundation of China 81973761, 82274593
6 · The paper itself

Abstract

backgroundEsophageal cancer (EC) is one of the deadliest malignancies worldwide. Gynostemma pentaphyllum Thunb. Makino (GpM) has been used in traditional Chinese medicine as a treatment for tumors and hyperlipidemia. Nevertheless, the active components and underlying mechanisms of anti-EC effects of GpM remain elusive.

objectiveThis study aims to determine the major active ingredients of GpM in the treatment of EC and to explore their molecular mechanisms by using network pharmacology, molecular docking, and in vitro experiments.

methodsFirstly, active ingredients and potential targets of GpM, as well as targets of EC, were screened in relevant databases to construct a compound-target network and a protein-protein interaction (PPI) network that narrowed down the pool of ingredients and targets. This was followed by gene ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Next, molecular docking, ADME and toxicity risk prediction, cell viability assays,

resultsThe screening produced a total of 21 active ingredients and 167 ingredient-related targets for GpM, along with 2653 targets for EC. The PPI network analysis highlighted three targets of interest, namely AKT1, TP53, and VEGFA, and the compound-target network identified three possible active ingredients: quercetin, rhamnazin, and isofucosterol. GO and EKGG indicated that the mechanism of action might be related to the PI3K/AKT signaling pathway as well as the regulation of cell motility and cell migration. Molecular docking and pharmacokinetic analyses suggest that quercetin and isoprostanoid sterols may have therapeutic value and safety for EC. The

conclusionOur findings indicate that GpM exerts its anti-tumor effect on EC by inhibiting EC cell migration and invasion via downregulation of the PI3K/AKT signaling pathway. Hence, we have reason to believe that GpM could be a promising candidate for the treatment of EC.

Indexed as

Antineoplastic Agents, PhytogenicDrugs, Chinese HerbalEsophageal NeoplasmsGynostemmaNetwork PharmacologyCell Line, TumorCell MovementCell ProliferationCell SurvivalDose-Response Relationship, DrugDrug Screening Assays, AntitumorHumansMolecular Docking SimulationProtein Interaction MapsAntineoplastic Agents, PhytogenicDrugs, Chinese Herbalesophageal cancerGynostemma pentaphyllumKYSE- 150.molecular dockingnetwork pharmacologyPI3K/AKT

Identifiers

PMID38243957
PMCPMC12174898
OpenAlexW4391067295

What OpenQuestion 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 OpenQuestion graph.