Evidence map›Paper›PMID 40255256›Full record

ArticleIn silico pharmacology2025

Unraveling the mechanism of core prescription in primary liver cancer: integrative analysis through data mining, network pharmacology, and molecular simulation.

Qingsi Zhao, Gaoyue Dong, Xinyue Zhang, Xing Gao, Hongyu Li, Zhongyuan Guo, Leilei Gong, Hong Yang

Abstract read
In one paragraph

Article in In silico pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

Qingsi Zhao *Yanjing Medical College, Capital Medical University, Beijing, 101300 China.
Gaoyue Dong *Yanjing Medical College, Capital Medical University, Beijing, 101300 China.
Xinyue ZhangYanjing Medical College, Capital Medical University, Beijing, 101300 China.
Xing GaoYanjing Medical College, Capital Medical University, Beijing, 101300 China.
Hongyu LiYanjing Medical College, Capital Medical University, Beijing, 101300 China.
Zhongyuan GuoCollege of Medicine, Henan University of Chinese Medicine, Zhengzhou, 450046 Henan China.
Leilei GongBeijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, 100026 China.
Hong YangYanjing Medical College, Capital Medical University, Beijing, 101300 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to identify core Traditional Chinese Medicine compound prescriptions (TCM CPs) for Primary Liver Cancer (PLC) and their underlying mechanisms. A comprehensive search was conducted using China National Knowledge Infrastructure (CNKI) and the Chinese Medical Code V5.0, identifying 151 TCM CPs. Medication frequency and association rules were analyzed with TCMICS V3.0, while active compounds were identified via TCMSP and TCMIP V2.0. Targets were predicted using Swiss Target Prediction, and disease targets from DisGeNET, OMIM, and GeneCards were cross-referenced. A protein-protein interaction (PPI) network was constructed, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis using DAVID. In the process of studying active compounds, an orthogonal experiment was carried out on the extraction process of relevant herbs. The results of the orthogonal experiment and range analysis showed that for the extraction rate of the extract and the content of paeoniflorin, the decoction cycles had the most significant impact, followed by soaking time and water volume. The optimal extraction conditions were determined as soaking time of 30 min, water volume of tenfold, and 3 decoction cycles. Under these conditions, the extract yield reached 42.49%, and the paeoniflorin content was 73.60 mg/25.02 g crude herb (equivalent to 2.94 mg/g). ANOVA analysis further confirmed the significance of these factors. The results revealed 109 common targets between TCM component targets and disease targets, with key targets including STAT3, SRC, AKT1, HRAS, and PIK3CA. Molecular docking showed strong binding affinities of paeoniflorin and 3,5,6,7-tetramethoxy-2-(3,4,5-trimethoxyphenyl) chromone to PLC targets, with ADME predictions favoring paeoniflorin. Furthermore, Molecular Dynamics (MD) simulations revealed that paeoniflorin maintains stable binding to the target proteins, demonstrating promising conformational stability. The CCK-8 assay demonstrated that the core TCM CP exerted a dose-dependent inhibitory effect on HepG2 cells. After 24 h of intervention, the IC Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-025-00352-2.

Indexed as

Data miningMolecular simulation validationNetwork pharmacologyPrimary liver cancerTraditional Chinese medicine compound prescription

Identifiers

PMID40255256
PMCPMC12003234

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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.