ArticleCombinatorial chemistry & high throughput screening2025
Integrated Network Pharmacology and
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.
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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.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- RepurposingACS omega · 2026Article
- Exploration of Fingerprints and Data Mining-based Prediction of Some Bioactive Compounds fromCurrent computer-aided drug design · 2025Article
- Advances in drug delivery systems for the management of gout and hyperuricemia.Frontiers in pharmacology · 2025Review
- Evaluation of the Potential Targets of Shenxian-Shengmai Oral Liquid in Treating Sick Sinus Syndrome Based on Network Pharmacology and Molecular Docking.Food science & nutrition · 2024Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundDioscorea septemloba Thunb. (DST) has demonstrated therapeutic potential in the treatment of gout and its associated complications. However, the underlying mechanisms of DST's pharmacological activity remain unclear. This study aims to investigate the pharmacological substances and network regulatory mechanisms of DST in treating gout and its complications using network pharmacology.
methodsAccording to ultra-high performance liquid chromatography coupled with hybrid quadrupole-Orbitrap mass spectrometry (UPLC-Q-Exactive Orbitrap-MS) data and Lipinski's rule of five, 24 bioactive phytochemicals from DST were identified. The targets of gout were retrieved from Gene Expression Omnibus (GEO), GeneCards, and DisGeNET databases, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG pathway) enrichment analysis. The Cytoscape network analysis was used to identify the primary pathological pathways and key targets. Finally, LeDock was used for molecular docking to verify the active components of DST and their core target proteins.
resultsDST contains several core active ingredients, such as tetrahydroimidazo[1,2-a]pyridine- 2,5-dione, diosgenin, beta-sitosterol, dioscorol B, montroumarin and 9,10-dihydro-5,7- dimethoxy-3,4-phenanthrenediol. Moreover, these active components were found to strongly bind to the key targets for treating gout and its complications, including HSP90AA1, STAT3, PTGS2, PPARG, MTOR, HIF1A, MMP9, ESR1, and TLR4. As a result, DST alleviates gout and its complications by inhibiting xanthine dehydrogenase (XDH) to reduce uric acid levels and regulating the HIF-1α, EZH2/STAT3, and COX-2/PPAR-γ pathways to reduce inflammation. Additionally, it also plays an analgesic role by regulating the neuroactive ligand-receptor interaction pathway and calcium ion signaling pathway.
conclusionThis study has provided insights into the underlying mechanisms of DST in the treatment of gout and its complications, which could serve as a scientific foundation for its clinical translation.
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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.