Evidence map›Paper›PMID 40718794›Full record

ArticleFrontiers in molecular biosciences2025

Integrating multi-dimensional data to reveal the mechanisms and molecular targets of baikening granules for treatment of pediatric influenza.

Zhaoyuan Gong, Qianzi Che, Mingzhi Hu, Tian Song, Lin Chen, Haili Zhang, Ning Liang, Huizhen Li, Guozhen Zhao, Lijiao Yan and 4 more

Abstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Zhaoyuan Gong *Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Qianzi Che *Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Mingzhi Hu *Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Tian SongInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Lin ChenInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Haili ZhangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Ning LiangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Huizhen LiInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Guozhen ZhaoInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Lijiao YanInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Xuefei ZhangInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Bin LiuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Jing GuoInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Nannan ShiInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Children are the main group affected by the influenza virus, posing challenges to their health. The high risk of viral variability, drug resistance, and drug development leads to a scarcity of therapeutic drugs. Baikening (BKN) granules are a marketed traditional Chinese medicine used to treat children's lung heat, asthma, whooping cough, etc. Therefore, exploring the potential mechanisms of BKN in treating pediatric influenza is of great significance for discovering new drugs. Methods: Through the database, we obtained differentially expressed genes (DEGs) between pediatric influenza and healthy samples, identified the components of BKN, and collected the targets. Target networks were built with the purpose of screening both targets and key components. Pathway and function enrichment were conducted on the relevant targets of BKN for treating pediatric influenza. BKN-related hub genes for influenza were discovered through DEGs, weighted gene co-expression network analysis (WGCNA), BKN-cluster WGCNA, and machine learning model. The accuracy of prediction efficiency and the value of BKN-related hub gene were validated through analysis of external datasets and receiver operating characteristics. Ultimately, simulations using molecular docking and molecular dynamics were used to forecast how active components will bind to hub genes. Result: A total of 20 candidate active compounds, 58 potential targets, and 3,819 DEGs were identified. The target network screened the top 10 key components and 6 core targets (PPARG, MMP2, GSK3B, PARP1, CCNA2, and IGF1). Potential target enrichment analysis indicated that BKN may be involved in AMPK signaling pathway, PI3K Akt signaling pathway, etc., to combat pediatric influenza. Subsequently, two hub genes (OTOF, IFI27) were obtained through WGCNA, BKN-cluster WGCNA, and machine learning models as potential biomarkers for BKN-related pediatric influenza. Two hub genes were found to have primary diagnostic value based on ROC curve analysis. Molecular docking confirmed the binding between BKN and hub gene. Molecular dynamics further revealed the stable binding between Peimisine and hub genes. Conclusion: BKN may alleviate pediatric influenza via key components targeting core targets (PPARG, MMP2, GSK3B, PARP1, CCNA2, and IGF1) and hub genes (OTOF, IFI27), with the involvement of feature genes-related pathways. These results have potential consequences for future research and clinical practice.

Indexed as

baikening granulesbioinformaticsmachine learningmolecular dockingmolecular dynamics simulationnetwork pharmacologypediatric influenza

Identifiers

PMID40718794
PMCPMC12289495

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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.