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中文摘要
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描述(由申请人提供):该提案的目标是通过结合计算和实验方法来预测和设计特定的蛋白质相互作用。为了降低问题的复杂性,我们将目标对准了由盘绕线圈介导的相互作用。螺旋线圈是一个简单而重要的相互作用基序,估计在所有蛋白质中约有3%-5%存在,包括许多对人类疾病重要的蛋白质。在过去的15年里,人们对它进行了广泛的研究。因此,现有的知识提供了一个框架,在其中尝试交互预测和设计的挑战性问题。该提案的具体目标是:(1)测量在人类和酵母bZIP转录因子中发现的卷曲之间的配对。这将使用大规模的蛋白质微阵列分析来完成。所得数据将用于开发从序列预测盘管-线圈相互作用的计算方法。BZIP交互屏幕还将为研究涉及人类癌基因的转录调控网络提供丰富的数据,包括Fos和Jun. (2)改进已有的蛋白质设计计算方法,使之更适合于设计相互作用专一性的问题。 3)使用目标2中的计算指导方法设计与目标人bZIP卷曲结构域特异结合的多肽,并对这些设计进行实验测试。这将提供设计的多肽与具有相似相互作用性质的自然产生的多肽(目标1)的比较。这也将构成对我们对螺旋线圈识别的基本理解的严格测试,并将为干扰转录调控网络提供有用的试剂。 (4)设计一种抑制人癌蛋白BcrAbl寡聚的多肽。螺旋线圈介导的bcr二聚化与95%以上的慢性粒细胞白血病有关。 总之,这些研究将提高我们对蛋白质相互作用特异性的分子基础的理解,并提供可用于合理改变蛋白质结构和功能的工具。所提出的方法可以广泛地应用于不同的域-域相互作用,因此我们所获得的见解将对蛋白质-蛋白质关联的总体研究具有广泛的意义。
英文摘要
DESCRIPTION (provided by applicant): The goal of this proposal is to predict and design specific protein interactions by using a combination of computational and experimental methods. To reduce the complexity of the problem, we target interactions mediated by the coiled coil. The coiled coil is a simple and important interaction motif estimated to occur in roughly 3-5% of all proteins, including many important for human disease. It has been studied extensively over the past 15 years. Consequently, existing knowledge provides a framework in which to attempt the challenging problems of interaction prediction and design. The specific aims of the proposal are: (1) To measure the pairings that occur among coiled coils found in human and yeast bZIP transcription factors. This will be accomplished using a large-scale protein microarray assay. The resulting data will be used to develop computational methods for predicting coiled-coil interactions from sequence. The bZIP interaction screen will also provide a wealth of data for the study of transcriptional regulatory networks that involve human oncogenes, including Fos and Jun. (2) To improve computational methods that have been developed for protein design so that these are more suitable for the problem of designing interaction specificity. 3) To use computationally-guided methods from Aim 2 to design peptides that bind specifically to targeted human bZIP coiled-coil domains, and to test these designs experimentally. This will provide a comparison of designed peptides with naturally occurring ones (Aim 1) that share similar interaction properties. It will also constitute a rigorous test of our basic understanding of coiled-coil recognition, and it will provide useful reagents for perturbing transcriptional regulatory networks. (4) To design a peptide that acts as an inhibitor of the oligomerization of BcrAbl, a human oncoprotein. The coiled coil-mediated dimerization of Bcr is implicated in more than 95% of chronic myelogenous leukemias. Together, these studies will improve our understanding of the molecular basis of protein interaction specificity and provide tools that can be used to rationally alter protein structure and function. The methods proposed can be applied to a wide range of different domain-domain interactions, so the insights that we achieve will have broad significance for the study of protein-protein associations generally.
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Computational and Experimental Investigation and Design of Protein Interaction Specificity
Mapping, modeling and manipulating the interactions of protein domains that bind short linear motifs
Mapping, modeling and manipulating the interactions of protein domains that bind short linear motifs
Computationally guided design of helical peptide interaction reagents
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