ROLE OF PROTEIN SOFT SPOTS IN LIGAND RECOGNITION AND INHIBITOR DESIGN

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。 背景：该项目旨在确定活性部位结构多态，或软点，以提供新的工具，用于研究配体识别和基于结构的药物设计。在大多数癌症中，a特定的激酶是假定的药物靶点(例如，用于慢性髓系白血病的Abl)。因为大多数激酶的活性位点在结构上是相似的，所以将特定的激酶的活性构象定位于细胞中的其他激酶可能是具有挑战性的。然而，从格列卫的例子中可以看出，稳定独特的、不活跃的蛋白质构象提供了一种有吸引力的替代范例。不幸的是，预测潜在的配体诱导的非结合蛋白质的结构重排是极其困难的，因为这项任务需要确定结构的集合，而不仅仅是最多人的构象。我建议通过结合和扩展现有的电子密度采样方法来解决这个问题，以生成用于X射线晶体数据的蛋白质结构系综。 目的：我们假设，通过有选择地采样电子密度，我们将能够识别蛋白质靶标的多个独特构象。这一新的工具可以用来研究配体结合的生物物理性质和特异性。它还可以用来帮助设计新的小分子，提高蛋白质折叠或功能家族中的特异性。 具体目标：(1)结合和扩展tau值&#65533；侧链无序的定量度量&#65533；和林格程序&#65533；一种将交替的侧链游离体构建为弱电子密度特征的方法&#65533；以识别和表征模型体系中的软点；(2)将钙调蛋白-肽复合体的电子密度分析与正交实验数据进行比较，以评估软点重排对结合特异性的影响；以及(3)应用电子密度采样来识别和表征潜在的配体诱导的重排作为蛋白质药物靶标结构中的软点。 研究设计：为了检测活性中心的漂移，我们将阐述两种新的方法&tau值和Ringer&#65533；来计算分析X射线电子密度。为了验证自由受体的电子密度包含关于结合态可及构象的结构信息的想法(S)，我们将比较游离钙调蛋白的结晶学、核磁共振和量热数据，以及五种不同多肽的复合体中的钙调蛋白。最后，我们将比较几种疾病相关蛋白在载脂蛋白形式和与各种类药物分子结合方面的作用。在每种情况下，我们都将预测哪些游离受体残基可以调节到不同的配体，然后使用结合构象来评估这些预测。一旦新方法被开发和验证，我们将进行一项前瞻性研究，我们将预测蛋白质MPtpA将如何对抑制剂类似物的结合做出反应，并使用X射线共晶体结构测试预测。 癌症相关性：由于包括激酶在内的可能的癌症靶点的活性部位已被证明作为其自然功能的一部分和对抑制剂结合的反应而重新排列，这些方法有可能为基于结构的药物设计提供强大的新工具，并促进对配体结合的生物物理理解。有了这项新的电子密度分析技术，我们将能够从单晶体结构预测这些重排，并将这一知识应用于开发具有更高特异性的治疗药物，以及提供对生物活性所需的结构重排机制的洞察。

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. Background: This project aims to identify active-site structural polymorphism, or �soft spots�, in order to provide new tools for use in the study of ligand recognition and structure-based drug design. In the majority of cancers, the a specific kinase is the putative drug target (e.g. Abl for chronic myeloid leukemia). Because the active sites of most kinases are structurally similar, targeting the active conformation of a particular kinase over others in the cell can be challenging. As can be seen in the example of Gleevec, however, stabilizing unique, inactive protein conformations provides an attactive alternate paradigm. Unfortunately, it is extremely difficult to predict potential ligand-induced structural rearrangements in unbound proteins, as this task requires determining ensembles of structures instead of just the most populated conformation. I propose to address this issue by combining and extending existing electron density sampling methods to generate ensembles of protein structures for X-ray crystallographic data. Objective: We hypothesize that by selectively sampling electron density, we will be able to identify multiple, unique conformations of protein targets. This new tool can then be used to investigate the biophysical properties of ligand binding and specificity. It can also be used to aid in designing new small molecules with increased specificity with in a protein fold or functional family. Specific Aims: (1) Combine and extend tau-values�a quantitative metric of side-chain disorder�and the Ringer program�a method for building alternate side chain rotamers into weak electron density features�to identify and characterize soft spots in model systems; (2) compare electron density analysis with orthogonal experimental data for calmodulin-peptide complexes to evaluate the effect of soft spot rearrangements on binding specificity; and (3) apply electron density sampling to identify and characterize potential ligand-induced rearrangements as soft spots in the apo structure of protein drug targets. Study Design: To detect active site excursions, we will elaborate two new methods�tau values and Ringer�to computationally analyze X-ray electron density. To test the idea that the electron density of free receptors contains structural information about accessible conformations of the bounds state(s), we will compare crystallographic, NMR and calorimetric data for free calmodulin to calmodulin in complex with five distinct peptides. Finally, we will compare several disease-related protein targets in both the apo form and bound to various drug-like molecules. In each case, we will predict which residues of the free receptor can adjust to different ligands, and then evaluate these predictions using the bound conformations. Once the new method has been developed and validated, we will perform a prospective study where we will predict how the protein MPtpA will respond to binding of inhibitor analogs and test the predictions using X-ray cocrystal structures. Cancer Relevance: Because the active sites of putative cancer targets, including kinases, have been shown to rearrange both as part of their natural function and in response to inhibitor binding, these methods have the potential to provide powerful new tools for structure-based drug design and to advance biophysical understanding of ligand binding. With this new electron density analysis technique, we will be able to predict these rearrangements from a single crystal structure and apply this knowledge both to develop therapeutics with improved specificity as well as provide insight into the mechanism of structural rearrangement necessary for biological activity.