SIGNALING BY NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET

雌激素受体非经典配体发出的信号检测新方法

基本信息

  • 批准号:
    8168088
  • 负责人:
  • 金额:
    $ 11.67万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-05-19 至 2011-04-30
  • 项目状态:
    已结题

项目摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Estrogens affect a large number of physiological functions and disease states. In addition to endogenous hormones, humans are exposed to a wide variety of estrogenic compounds in the diet, environment, and pharmaceuticals. These non-classical ligands for the estrogen receptor (ER) can have major effects on human health. Aim 1: Efficient methods of testing for estrogenic activity are important for drug development, environmental testing, and research on receptor functions and mechanisms. Yeast-based assays using exogenously expressed ERs and reporter genes are inexpensive and widely used, but have the defect that the response to some SERMS (selective estrogen receptor modulators) and phytoestrogens is very different from that seen in mammalian cells. This project will develop and test a reporter system in the nematode C. elegans, which is easily grown in culture. It is hypothesized that the closer evolutionary relationship of humans and C. elegans will enable this system to produce more relevant results than yeast-based assays, but retain the advantages of simplicity and low cost. Aim 2: Although there is substantial human exposure to non-classical ER ligands, their modes of action are incompletely understood. SERMs such as tamoxifen often have biphasic dose-response curves, with ER agonism at low concentrations and antagonism at high concentrations. It has been proposed that in addition to occupying the hormone-binding pocket of ER, these compounds bind (with lower affinity) to a 2nd site that mediates antagonism. Some phytoestrogens have a similar biphasic effect, suggesting that they are natural ligands for this site. This project will determine if phytoestrogens and ANGELS (activators of non-genotropic estrogen-like signaling, a new class of ER-targeted drugs) compete with SERMS for binding to the 2nd site, identify and ablate the site via targeted mutagenesis, and characterize the significance of the site in ER function by reporter gene assays, microarray analysis and real-time PCR.
这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金, 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 雌激素影响大量的生理功能和疾病状态。除了内源性激素,人类还暴露在饮食、环境和药物中的各种雌激素化合物中。这些非经典的雌激素受体(ER)配体可以对人类健康产生重大影响。目的1:有效的雌激素活性检测方法对药物开发、环境检测以及受体功能和机制的研究具有重要意义。使用外源表达的ER和报告基因的酵母检测方法价格低廉,应用广泛,但存在着缺陷,即对某些选择性雌激素受体调节剂(SERMS)和植物雌激素的反应与哺乳动物细胞中的反应非常不同。该项目将在线虫体内开发和测试一种报告系统,这种线虫很容易在培养中生长。假设人类和线虫的进化关系更密切,将使该系统能够产生比基于酵母的检测更相关的结果,但保留了简单和低成本的优势。目的2:尽管人类大量接触非经典内质网配体,但其作用模式尚不完全清楚。他莫昔芬等SERM通常具有双相剂量-反应曲线,在低浓度时具有ER激活性,在高浓度时具有拮抗作用。有人提出,除了占据内质网的激素结合口袋外,这些化合物还(亲和力较低)结合到第二个介导拮抗的位置。一些植物雌激素具有类似的双相效应,表明它们是该部位的天然配体。本项目将确定植物雌激素和Angels(非遗传性雌激素样信号的激活物,一种新型的ER靶向药物)是否与SERMS竞争结合第二个位点,通过靶向突变识别和去除该位点,并通过报告基因分析、微阵列分析和实时荧光PCR表征该位点在ER功能中的意义。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

BARRY D GEHM其他文献

BARRY D GEHM的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('BARRY D GEHM', 18)}}的其他基金

SIGNALING BY NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET
雌激素受体非经典配体的信号传导检测新方法
  • 批准号:
    7959425
  • 财政年份:
    2009
  • 资助金额:
    $ 11.67万
  • 项目类别:
SIGNALING BY NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET
雌激素受体非经典配体的信号传导检测新方法
  • 批准号:
    7725057
  • 财政年份:
    2008
  • 资助金额:
    $ 11.67万
  • 项目类别:
SIGNALING BY NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET
雌激素受体非经典配体发出的信号检测新方法
  • 批准号:
    7610002
  • 财政年份:
    2007
  • 资助金额:
    $ 11.67万
  • 项目类别:
SIGNALING BY NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET
雌激素受体非经典配体的信号传导检测新方法
  • 批准号:
    7381384
  • 财政年份:
    2006
  • 资助金额:
    $ 11.67万
  • 项目类别:
NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET & MECH
雌激素受体的非经典配体检测新方法
  • 批准号:
    7170598
  • 财政年份:
    2005
  • 资助金额:
    $ 11.67万
  • 项目类别:
SIGNALING BY NON-CLASSICAL LIGANDS OF ESTROGEN RECEPTOR NOVEL APPROACHES TO DET
雌激素受体非经典配体的信号传导检测新方法
  • 批准号:
    6981564
  • 财政年份:
    2003
  • 资助金额:
    $ 11.67万
  • 项目类别:

相似海外基金

Applications of Deep Learning for Binding Affinity Prediction
深度学习在结合亲和力预测中的应用
  • 批准号:
    2887848
  • 财政年份:
    2023
  • 资助金额:
    $ 11.67万
  • 项目类别:
    Studentship
Metalloenzyme binding affinity prediction with VM2
使用 VM2 预测金属酶结合亲和力
  • 批准号:
    10697593
  • 财政年份:
    2023
  • 资助金额:
    $ 11.67万
  • 项目类别:
Building a binding community - Capacity and capability for affinity and kinetic analysis of molecular interactions.
建立结合社区 - 分子相互作用的亲和力和动力学分析的能力和能力。
  • 批准号:
    MR/X013227/1
  • 财政年份:
    2022
  • 资助金额:
    $ 11.67万
  • 项目类别:
    Research Grant
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutions
使用动态网络模型定量预测由长程氨基酸取代引起的结合亲和力/特异性的变化
  • 批准号:
    10797940
  • 财政年份:
    2022
  • 资助金额:
    $ 11.67万
  • 项目类别:
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutions
使用动态网络模型定量预测由长距离氨基酸取代引起的结合亲和力/特异性的变化
  • 批准号:
    10502084
  • 财政年份:
    2022
  • 资助金额:
    $ 11.67万
  • 项目类别:
Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutions
使用动态网络模型定量预测由长距离氨基酸取代引起的结合亲和力/特异性的变化
  • 批准号:
    10707418
  • 财政年份:
    2022
  • 资助金额:
    $ 11.67万
  • 项目类别:
Binding affinity of inositol phosphate analogs to protein toxin TcdB
磷酸肌醇类似物与蛋白质毒素 TcdB 的结合亲和力
  • 批准号:
    573604-2022
  • 财政年份:
    2022
  • 资助金额:
    $ 11.67万
  • 项目类别:
    University Undergraduate Student Research Awards
Computational predictions of thermostability and binding affinity changes in enzymes
酶热稳定性和结合亲和力变化的计算预测
  • 批准号:
    2610945
  • 财政年份:
    2021
  • 资助金额:
    $ 11.67万
  • 项目类别:
    Studentship
I-Corps: Physics-Based Binding Affinity Estimator
I-Corps:基于物理的结合亲和力估计器
  • 批准号:
    2138667
  • 财政年份:
    2021
  • 资助金额:
    $ 11.67万
  • 项目类别:
    Standard Grant
Computational modelling and simulation of antibodies to enhance binding affinity of a potential Burkholderia pseudomallei therapeutic
抗体的计算模型和模拟,以增强潜在的鼻疽伯克霍尔德氏菌治疗剂的结合亲和力
  • 批准号:
    2750554
  • 财政年份:
    2021
  • 资助金额:
    $ 11.67万
  • 项目类别:
    Studentship
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了