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的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 背景：本项目旨在识别活性位点结构多态性，或软点，以提供新的工具，用于配体识别和基于结构的药物设计的研究。 在大多数癌症中，特异性激酶是推定的药物靶标（例如，慢性髓性白血病的Abl）。 由于大多数激酶的活性位点在结构上相似，因此靶向细胞中特定激酶的活性构象可能具有挑战性。 然而，从格列卫的例子中可以看出，稳定独特的、无活性的蛋白质构象提供了一种攻击性的替代范例。 不幸的是，预测未结合蛋白质中潜在的配体诱导的结构重排是非常困难的，因为这项任务需要确定结构的集合，而不仅仅是最常见的构象。 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射线晶体学数据的蛋白质结构的集合。 目的：我们假设，通过选择性地采样电子密度，我们将能够识别多个，独特的构象的蛋白质目标。 这种新的工具可以用来研究配体结合和特异性的生物物理特性。 它也可以用于帮助设计新的小分子，在蛋白质折叠或功能家族中具有增加的特异性。 具体目标： (1)联合收割机和扩展tau值，侧链紊乱的定量度量和Ringer程序，用于将交替侧链旋转异构体构建为弱电子密度特征的方法，以识别和表征模型系统中的软点;（2）将钙调蛋白-肽复合物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;和（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的apo结构中的软点。 研究设计：为了检测活性位点偏移，我们将阐述两种新的方法tau值和Ringer来计算分析X射线电子密度。 为了测试游离受体的电子密度包含关于束缚态的可接近构象的结构信息的想法，我们将比较游离钙调素与钙调素与五种不同肽的复合物的晶体学、NMR和量热数据。 最后，我们将比较几种疾病相关的蛋白质靶点，包括载脂蛋白形式和与各种药物样分子结合的靶点。 在每种情况下，我们将预测哪些残基的游离受体可以调整不同的配体，然后评估这些预测使用的结合构象。 一旦新方法得到开发和验证，我们将进行一项前瞻性研究，预测蛋白质MPtpA将如何响应抑制剂类似物的结合，并使用X射线共晶结构测试预测。 癌症相关性：由于公认的癌症靶点（包括激酶）的活性位点已被证明是其天然功能的一部分，并响应于抑制剂结合而重排，因此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。 有了这种新的电子密度分析技术，我们将能够从单晶结构中预测这些重排，并将这些知识应用于开发具有改进特异性的治疗方法，以及深入了解生物活性所需的结构重排机制。

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.