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.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 背景：该项目旨在识别活性位点结构多态性或“软点”，以便为配体识别和基于结构的药物设计研究提供新工具。 在大多数癌症中，特定激酶是假定的药物靶标（例如慢性粒细胞白血病的 Abl）。 由于大多数激酶的活性位点在结构上相似，因此针对细胞中特定激酶相对于其他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有吸引力的替代范例。 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极其困难的，因为这项任务需要确定结构的整体，而不仅仅是最常见的构象。 我建议通过组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 X 射线晶体学数据的蛋白质结构集合。 目的：我们假设通过选择性地采样电子密度，我们将能够识别蛋白质靶标的多种独特构象。 这种新工具可用于研究配体结合和特异性的生物物理特性。 它还可用于帮助设计在蛋白质折叠或功能家族中具有更高特异性的新小分子。 具体目标：(1) 结合并扩展 tau 值（侧链无序的定量度量）和 Ringer 程序（一种将替代侧链旋转异构体构建成弱电子密度特征的方法），以识别和表征软模型系统中的点； (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) 应用电子密度采样来识别和表征潜在的配体诱导重排，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，我们将详细阐述两种新方法——tau 值和 Ringer——以计算分析 X 射线电子密度。 为了检验游离受体的电子密度包含有关束缚态可接近构象的结构信息的观点，我们将比较游离钙调蛋白与与五种不同肽复合的钙调蛋白的晶体学、NMR 和量热数据。 最后，我们将比较几种与疾病相关的 apo 形式的蛋白质靶标以及与各种药物样分子结合的蛋白质靶标。 在每种情况下，我们将预测游离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。 一旦新方法被开发出来并得到验证，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：由于假定的癌症靶标（包括激酶）的活性位点已被证明会重新排列，作为其自然功能的一部分并响应抑制剂结合，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学理解。 通过这种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，并应用这些知识来开发具有更高特异性的治疗方法，并深入了解生物活性所需的结构重排机制。