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DEVELOPMENT OF HIGHLY SELECTIVE PROTEIN AND LIPID KINASE INHIBITORS

DEVELOPMENT OF HIGHLY SELECTIVE PROTEIN AND LIPID KINASE INHIBITORS
高选择性蛋白质和脂质激酶抑制剂的开发
批准号:
8169783
负责人:
KEVAN M. SHOKAT
金额:
$0.18万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-12 至 2011-05-31

项目摘要

项目成果

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中文摘要
翻译
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。 蛋白质和脂肪蛋白是细胞信息的重要传递者。人类基因组中有500多个蛋白激酶和30多个脂肪激酶。我们感兴趣的是开发了解和破译激酶介导的信号通路的化学方法。该项目的目标是开发高选择性的小分子蛋白和脂蛋白激酶抑制剂。这些小分子被设计成适合于激酶的三磷酸腺苷结合口袋。我们使用合成有机化学和结构生物学(X射线共晶体结构)相结合的方法来开发这些分子。我们通常使用五步或更少的集中合成,每个设计大约有20个候选抑制剂。这项工作需要中间体和最终产品的标准结构表征,以便出版或结构分配。通常情况下,我们需要高分辨率的小分子质谱仪。它们通常在结构上高度相关,允许参数优化并同时用于多个样本。
英文摘要
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. Protein and lipid kinases are important transducers of cellular information. There are 500+ protein kinases and 30+ lipid kinases in the human genome. We are interested in developing chemical approaches for understanding and deciphering kinase mediated signaling pathways. The goal of this project is to develop highly selective small molecule protein and lipid kinase inhibitors. These small molecules are designed to fit in the ATP binding pocket of the kinases. We use synthetic organic chemistry coupled with structural biology (X-ray co-crystal structures) to develop these molecules. We typically use focused syntheses of five or fewer steps and make on the order of 20 candidate inhibitors per design. This work requires standard structural characterization of the intermediates and final products for publication or structural assignment purposes. Typically we need high resolution mass spectrometry of the small molecules. They are often highly structurally related, allowing for parameters to be optimized and used for a number of samples at once.
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