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基于细胞的Tox21 10K文库中芳香酶抑制剂的高通量筛选

Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K Library.

作者信息

Chen Shiuan, Hsieh Jui-Hua, Huang Ruili, Sakamuru Srilatha, Hsin Li-Yu, Xia Menghang, Shockley Keith R, Auerbach Scott, Kanaya Noriko, Lu Hannah, Svoboda Daniel, Witt Kristine L, Merrick B Alex, Teng Christina T, Tice Raymond R

机构信息

*Department of Cancer Biology, Beckman Research Institute of the City of Hope, Duarte, California 91010;

Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709;

出版信息

Toxicol Sci. 2015 Oct;147(2):446-57. doi: 10.1093/toxsci/kfv141. Epub 2015 Jul 3.

Abstract

Multiple mechanisms exist for endocrine disruption; one nonreceptor-mediated mechanism is via effects on aromatase, an enzyme critical for maintaining the normal in vivo balance of androgens and estrogens. We adapted the AroER tri-screen 96-well assay to 1536-well format to identify potential aromatase inhibitors (AIs) in the U.S. Tox21 10K compound library. In this assay, screening with compound alone identifies estrogen receptor alpha (ERα) agonists, screening in the presence of testosterone (T) identifies AIs and/or ERα antagonists, and screening in the presence of 17β-estradiol (E2) identifies ERα antagonists. Screening the Tox-21 library in the presence of T resulted in finding 302 potential AIs. These compounds, along with 31 known AI actives and inactives, were rescreened using all 3 assay formats. Of the 333 compounds tested, 113 (34%; 63 actives, 50 marginal actives) were considered to be potential AIs independent of cytotoxicity and ER antagonism activity. Structure-activity analysis suggested the presence of both conventional (eg, 1, 2, 4, - triazole class) and novel AI structures. Due to their novel structures, 14 of the 63 potential AI actives, including both drugs and fungicides, were selected for confirmation in the biochemical tritiated water-release aromatase assay. Ten compounds were active in the assay; the remaining 4 were only active in high-throughput screen assay, but with low efficacy. To further characterize these 10 novel AIs, we investigated their binding characteristics. The AroER tri-screen, in high-throughput format, accurately and efficiently identified chemicals in a large and diverse chemical library that selectively interact with aromatase.

摘要

内分泌干扰存在多种机制;一种非受体介导的机制是通过对芳香化酶的影响,芳香化酶是维持体内雄激素和雌激素正常平衡的关键酶。我们将AroER三筛选96孔检测法调整为1536孔形式,以在美国毒物21 10K化合物库中鉴定潜在的芳香化酶抑制剂(AI)。在该检测中,单独用化合物筛选可鉴定雌激素受体α(ERα)激动剂,在睾酮(T)存在下筛选可鉴定AI和/或ERα拮抗剂,在17β-雌二醇(E2)存在下筛选可鉴定ERα拮抗剂。在T存在下筛选毒物21库,发现了302种潜在的AI。这些化合物,连同31种已知的AI活性和非活性物质,使用所有3种检测形式进行了重新筛选。在测试的333种化合物中,113种(34%;63种活性物质,50种边缘活性物质)被认为是潜在的AI,与细胞毒性和ER拮抗活性无关。构效分析表明存在传统(如1,2,4-三唑类)和新型AI结构。由于其新颖的结构,63种潜在的AI活性物质中的14种,包括药物和杀菌剂,被选用于生化氚水释放芳香化酶检测中进行确认。10种化合物在检测中具有活性;其余4种仅在高通量筛选检测中有活性,但效力较低。为了进一步表征这10种新型AI,我们研究了它们的结合特性。高通量形式的AroER三筛选准确有效地鉴定了一个大型多样化学库中与芳香化酶选择性相互作用的化学物质。

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