Evidence map›Paper›PMID 25047514›Full record

ArticleActa pharmacologica Sinica2014

Discovery of novel aromatase inhibitors using a homogeneous time-resolved fluorescence assay.

Jin-zi Ji, Ke-jing Lao, Jie Hu, Tao Pang, Zhen-zhou Jiang, Hao-liang Yuan, Jing-shan Miao, Xin Chen, Shan-shan Ning, Hua Xiang and 3 more

Abstract read
In one paragraph

Article in Acta pharmacologica Sinica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
  6. Article
  7. Review
  8. Review
  9. Chemoprevention of Breast Cancer by Dietary Polyphenols.Molecules (Basel, Switzerland) · 2015
    Review
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

13 authors.

Jin-zi JiJiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China.
Ke-jing LaoDepartment of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
Jie HuJiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China.
Tao Pang1] Jiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China [2] Jiangsu Center for Pharmacodynamics Research and Evaluation, China Pharmaceutical University, Nanjing 210009, China.
Zhen-zhou Jiang1] Jiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China [2] Key Laboratory of Drug Quality Control and Pharmacovigilance (China Pharmaceutical University), Ministry of Education, Nanjing 210009, China.
Hao-liang YuanLaboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, Nanjing 210009, China.
Jing-shan MiaoJiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China.
Xin ChenJiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China.
Shan-shan NingDepartment of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
Hua XiangDepartment of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, Nanjing 210009, China.
Yu-meng GuoJiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China.
Ming Yan1] Jiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China [2] Jiangsu Center for Pharmacodynamics Research and Evaluation, China Pharmaceutical University, Nanjing 210009, China.
Lu-yong Zhang1] Jiangsu Center for Drug Screening, China Pharmaceutical University, Nanjing 210009, China [2] State Key laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimAromatase is an important target for drugs to treat hormone-dependent diseases, including breast cancer. The aim of this study was to develop a homogeneous time-resolved fluorescence (HTRF) aromatase assay suitable for high-throughput screening (HTS).

methodsA 384-well aromatase HTRF assay was established, and used to screen about 7000 compounds from a compound library. Anti-proliferation activity of the hit was evaluated using alamarBlue(R) assay in a hormone-dependent breast cancer cell line T47D. Molecular docking was conducted to elucidate the binding mode of the hit using the Discovery Studio program.

resultsThe Z' value and signal to background (S/B) ratio were 0.74 and 5.4, respectively. Among the 7000 compounds, 4 hits (XHN22, XHN26, XHN27 and triptoquinone A) were found to inhibit aromatase with IC50 values of 1.60±0.07, 2.76±0.24, 0.81±0.08 and 45.8±11.3 μmol /L, respectively. The hits XHN22, XHN26 and XHN27 shared the same chemical scaffold of 4-imidazolyl quinoline. Moreover, the most potent hit XHN27 at 10 and 50 μmol/L inhibited the proliferation of T47D cells by 45.3% and 35.2%, respectively. The docking study revealed that XHN27 docked within the active site of aromatase and might form a hydrogen bond and had a π-cation interaction with amino acid residues of the protein.

conclusionXHN27, an imidazolyl quinoline derivative of flavonoid, is a potent aromatase inhibitor with anti-proliferation activity against breast cancer in vitro. The established assay can be used in HTS for discovering novel aromatase inhibitor.

Indexed as

AromataseAromatase InhibitorsBreastBreast NeoplasmsCell Line, TumorCell ProliferationDrug Screening Assays, AntitumorFemaleFlavonoidsHigh-Throughput Screening AssaysHumansMolecular Docking SimulationQuinolinesSmall Molecule LibrariesSpectrometry, FluorescenceAromataseAromatase InhibitorsFlavonoidsQuinolinesSmall Molecule Libraries

Identifiers

PMID25047514
PMCPMC4125720

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.