ArticleHeliyon2023
Uncovering the mechanism of Qidan Dihuang Granule in the treatment of diabetic kidney disease combined network pharmacology, UHPLC-MS/MS with experimental validation.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- [Different Astragalus medicinal pairs improve diabetic nephropathy in mice by regulating lipid peroxidation through PTGS2].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- Shensu IV maintains the integrity of the glomerular filtration barrier and exerts renal protective effects by regulating endogenous hydrogen sulfide levels.Frontiers in pharmacology · 2024Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aim: Diabetic Kidney Disease (DKD) is a common microvascular complication of diabetes mellitus. Multi-center, randomized controlled trials have shown that Qidan Dihuang Granule (QDDHG) reduces the levels of albuminuria of DKD. However, the specific mechanisms of QDDHG on DKD are not clarified. Thus, this study utilized network pharmacology, UHPLC-MS/MS (Ultra-High Performance Liquid Chromatography - Mass Spectrometry) and animal experiments to reveal the mechanisms of QDDHG on DKD. Experimental procedure: Screening and retrieving active ingredients and corresponding targets of QDDHG on DKD through the TCMSP, ETCM, Disgenet, GeneCards, Omim and DrugBank databases. The PPI were performed with BioGrid, STRING, OmniPath, InWeb-IM. AutoDock Vina molecular docking module to estimate the validation from the compounds and target proteins. Free energy to estimate the binding affinity for identified compounds and target proteins. The ingredients of QDDHG were analyzed utilizing UHPLC-MS/MS. Results and conclusion: The results demonstrated that QDDHG has 18 active compounds and 13 target proteins of QDDHG exerted a crucial role in treatment of DKD. QDDHG affect the multiple biological processes included cellular response to lipid, response to oxidative stress, and various pathways, such as AGE-RAGE, PI3K-Akt, MAPK, TNF, EGFR, STAT3. The results of UHPLC-MS/MS showed that six ingredients predicted by network pharmacology were also verified in experiment.
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Registered trials
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