Evidence map›Paper›PMID 39722812›Full record

ArticleFrontiers in endocrinology2024

Potential candidates from a functional food

Meilin Chen, Xiaomei Chen, Qinghong Chen, Chenyang Chu, Shuxuan Yang, Chuanghai Wu, Yanting You, Andrew Hung, Angela Wei Hong Yang, Xiaomin Sun and 4 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. 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
  2. IntegratedDrug target insights
    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

14 authors.

Meilin Chen *School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Xiaomei Chen *School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Qinghong Chen *School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Chenyang ChuSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Shuxuan YangSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Chuanghai WuSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Yanting YouSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Andrew HungSchool of Science, STEM College, RMIT University, Melbourne, VIC, Australia.
Angela Wei Hong YangSchool of Health and Biomedical Sciences, STEM College, RMIT University, Bundoora, VIC, Australia.
Xiaomin SunSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Lin ZhouEndocrinology Department, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xiaoshan ZhaoSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Hong LiSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
Yanyan LiuSchool of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Hyperuricemia (HUA) is a metabolic syndrome caused by purine metabolism disorders. Methods: Through network pharmacology, ZP's potential targets and mechanisms for HUA treatment were identified. Databases like TCMSP, UniProt, and Swiss Target Prediction were utilized for ZP's active ingredients and targets. HUA-related targets were filtered using GeneCards, Drugbank, and Open Targets. Core targets for ZP's HUA treatment were mapped in a PPI network and analyzed with Cytoscape. GO and KEGG pathway enrichments were conducted on intersected targets via DAVID. Molecular docking and virtual screening were performed to find optimal binding pockets, and ADMET screening assessed compound safety. Molecular dynamics simulations confirmed compound stability in binding sites. Results: We identified 81 ZP active ingredient targets, 140 HUA-related targets, and 6 drug targets, with xanthine dehydrogenase (XDH) as the top core target. Molecular docking revealed ZP's active ingredients had strong binding to XDH. Virtual screening via Protein plus identified 48 compounds near the optimal binding pocket, with 2'-methylacetophenone, ledol, beta-sitosterol, and ethyl geranate as the most promising. Molecular dynamics simulations confirmed binding stability, suggesting ZP's potential in HUA prevention and the need for further experimental validation. Conclusion: Our study provides foundations for exploring the mechanism of the lowering of uric acid by ZP and developing new products of ZP. The role of ZP in the diet may provide a new dietary strategy for the prevention of HUA, and more experimental studies are needed to confirm our results in the future.

Indexed as

HyperuricemiaMolecular Docking SimulationMolecular Dynamics SimulationNetwork PharmacologyFunctional FoodHumanscomplementary and alternative medicinehyperuricemiamedicine and food homologous plantmolecular dockingmolecular dynamics simulationZanthoxylum bungeanum

Identifiers

PMID39722812
PMCPMC11668583

What OpenQuestion holds

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Registered trials

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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.