ArticleACS omega2022
Network Analysis of the Herb-Drug Interactions of Citrus Herbs Inspired by the "Grapefruit Juice Effect".
Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Pharmacokinetic Profile of Extracts from the Chayote (Molecules (Basel, Switzerland) · 2025Article
- A comprehensive landscape of AI applications in broad-spectrum drug interaction prediction: a systematic review.Journal of cheminformatics · 2025Review
- LC-MS-based metabolomics for detecting adulteration inFood chemistry: X · 2025Article
- Article
- Article
- Citrus Waste as Source of Bioactive Compounds: Extraction and Utilization in Health and Food Industry.Molecules (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study was performed to investigate the herb-drug interactions (HDIs) of citrus herbs (CHs), which was inspired by the "grapefruit (GF) juice effect". Based on network analysis, a total of 249 components in GF and 159 compounds in CHs exhibited great potential as active ingredients. Moreover, 360 GF-related genes, 422 CH-related genes, and 111 genes associated with drug transport and metabolism were collected, while 25 and 26 overlapping genes were identified. In compound-target networks, the degrees of naringenin, isopimpinellin, apigenin, sinensetin, and isoimperatorin were higher, and the results of protein-protein interaction indicated the hub role of UGT1A1 and CYP3A4. Conventional drugs such as erlotinib, nilotinib, tamoxifen, theophylline, venlafaxine, and verapamil were associated with GF and CHs via multiple drug transporters and drug-metabolizing enzymes. Remarkably, GF and CHs shared 48 potential active compounds, among which naringenin, tangeretin, nobiletin, and apigenin possessed more interactions with targets. Drug metabolism by cytochrome P450 stood out in the mutual mechanism of GF and CHs. Molecular docking was utilized to elevate the protein-ligand binding potential of naringenin, tangeretin, nobiletin, and apigenin with UGT1A1 and CYP3A4. Furthermore, in vitro experiments demonstrated their regulating effect. Overall, this approach provided predictions on the HDIs of CHs, and they were tentatively verified through molecular docking and cell tests. Moreover, there is a demand for clinical and experimental evidence to support the prediction.
Identifiers
What OpenQuestion holds
Registered trials
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.