ROLE OF PROTEIN SOFT SPOTS IN LIGAND RECOGNITION AND INHIBITOR DESIGN

蛋白质软点在配体识别和抑制剂设计中的作用

• 批准号: 8170537
• 负责人: THOMAS C ALBER
• 金额: $ 1.79万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170537
• 关键词: Active Sites; Address; Binding; Biological; Biological Models; Calmodulin; Cells; Chronic Myeloid Leukemia; Complex; Computer Retrieval of Information on Scientific Projects Database; DNA Sequence Rearrangement; Data; Disease; Drug Delivery Systems; Drug Design; Family; Funding; Genetic Polymorphism; Gleevec; Grant; Institution; Knowledge; Ligand Binding; Ligands; Malignant Neoplasms; Methods; Metric; Molecular Conformation; Peptides; Pharmaceutical Preparations; Phosphotransferases; Property; Prospective Studies; Protein Conformation; Proteins; Research; Research Design; Research Personnel; Resources; Roentgen Rays; Role; Sampling; Side; Source; Specificity; Spottings; Structure; Techniques; Testing; Therapeutic; United States National Institutes of Health; analog; base; design; electron density; improved; inhibitor/antagonist; insight; programs; protein folding; protein structure; receptor; response; small molecule; tau Proteins; tool

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.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 背景：该项目旨在确定主动地点的结构多态性或“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，特定的激酶是推定的药物靶标（例如，用于慢性髓样白血病的ABL）。 由于大多数激酶的活性位点在结构上是相似的，因此针对细胞中其他激酶的主动构象的靶向可能具有挑战性。 但是，在Gleevec的示例中可以看出，稳定独特的，无活跃的蛋白质构型提供了一种可达到的替代范式。 不幸的是，很难预测未结合蛋白质中可能的配体诱导的结构重排，因为此任务需要确定结构的集合，而不仅仅是人口最多的构象。 我建议通过结合和扩展现有的电子密度采样方法来解决此问题，以生成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采样电子密度，我们将能够识别蛋白质靶标的多个独特的构象。 然后，该新工具可用于研究配体结合和特异性的生物物理特性。 它也可以用来帮助设计具有蛋白质折叠或功能家族中特异性提高的新小分子。 具体目的：（1）将tau-values（侧链障碍的定量度量标准）和林格（Ringer Program）组合在一起 - 一种将替代侧链旋转旋转剂构建为弱电子密度特征的方法 - 识别和表征模型系统中的软点； （2）将电子密度分析与钙调蛋白肽复合物的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； （3）应用电子密度采样，以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：为了检测活动现场偏移，我们将详细说明两种新方法 - tau值和铃声 - 到计算分析X射线电子密度。 为了测试自由受体的电子密度包含有关边界状态的可及构象的结构信息，我们将比较晶体学，NMR和量热量数据的自由钙调蛋白与复合物中的钙调蛋白与五个不同的肽。 最后，我们将比较Apo形式的几种与疾病相关的蛋白质靶标，并与各种药物样分子结合。 在每种情况下，我们将预测自由受体的哪些残基可以适应不同的配体，然后使用结合构象评估这些预测。 一旦开发和验证了新方法，我们将进行一项前瞻性研究，我们将预测蛋白质MPTPA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：由于包括激酶在内的假定癌症靶标的活跃部位已被证明是其自然功能的一部分和对抑制剂结合的响应，因此这些方法具有为基于结构的药物设计提供强大的新工具，并可以提高对配体结合的生物物理学理解。 借助这种新的电子密度分析技术，我们将能够从单晶体结构中预测这些重排，并应用这些知识来开发具有提高特异性的治疗剂，并洞悉生物活性所需的结构重排机制。