Dynamics of Ligand Binding and Protein Kinase Regulation

配体结合动力学和蛋白激酶调节

• 批准号: 10204514
• 负责人: Markus A Seeliger
• 金额: $ 40.77万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-15 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10204514
• 关键词: Affect; Affinity; Binding; Binding Proteins; Biological; Biological Assay; Biological Process; Biology; Catalytic Domain; Cells; Chemicals; Clinical; Collaborations; Computer Models; Computing Methodologies; Crystallization; Cyclic AMP-Dependent Protein Kinases; Data; Data Set; Development; Disease; Dissociation; Drug Modelings; Drug resistance; Enzymes; Family; Foundations; Goals; Health; Human; In Vitro; Kinetics; Knowledge; Ligand Binding; Malignant Neoplasms; Molecular; Molecular Conformation; Mutation; Pharmaceutical Preparations; Phenotype; Phosphotransferases; Process; Protein Engineering; Protein Kinase; Protein Tyrosine Kinase; Proteins; Public Health; Regulation; Research; Roentgen Rays; Role; Signal Pathway; Signal Transduction; Specificity; Structural Protein; Structure; Testing; design; inhibitor/antagonist; kinase inhibitor; pharmacokinetics and pharmacodynamics; pressure; protein structure; resistance mechanism; resistance mutation; src-Family Kinases; therapeutic target

PROJECT SUMMARY. Protein kinases are a large family of ubiquitous signaling enzymes in human cells. Their dysregulation often underlies diseases such as cancer, making them excellent therapeutic targets. However, the high structural and sequence conservation of the protein kinase catalytic domains has complicated the development of specific inhibitors. Many clinically-successful kinase inhibitors achieve specificity in part by binding only to distinct kinase conformations. While the analysis of thousands of X-ray crystal structures of protein kinases has shown that a single kinase domain can access different active and inactive conformations, little is known about how kinases interconvert between the conformations. The rationale of this proposal is that a quantitative understanding of the stability of these conformations and the dynamics of their interconversion are key to understanding kinase activity, regulation, ligand binding and drug resistance in health and disease states. The objective of this project is to obtain a comprehensive understanding of the role of conformational dynamics in kinase function, regulation and drug resistance through altered drug dissociation rates. This proposal is part of a continuum of research centered around three questions: Q1: How do regulatory domains, interacting proteins and disease-relevant mutations affect the conformational dynamics of tyrosine kinases? Our goal is to determine how the solution dynamics of Src kinase domain responds to these biologically important perturbations. Q2: What are the molecular and cellular determinants of ligand-binding kinetics? We will test our computational model for the drug binding process experimentally, both in vitro and in cells, by assessing drug affinities and binding and dissociation kinetics. Our goal is to determine quantitative parameters for the drug binding process and how the alteration of these parameters by mutation underlies drug resistance. Q3: How can phenotypic clustering of inhibition data be used to reveal hidden kinase features? Our goal is to mine kinome-wide inhibition datasets to group kinases by their inhibition phenotype, which reflects on the evolutionary pressure and adaption that other biological functions impose on kinases. We will use structural approaches (X-ray and NMR), cellular drug binding and activity assays, ligand binding kinetics, protein engineering, chemical biology and diverse computational methods. A network of productive collaborations supports this project. The impact of this project is to provide clinicians with the mechanism of resistance mutations, medicinal chemists with kinase inhibitor pharmacodynamics and pharmacokinetics and cell biologists with parameters to understand kinase signaling. The long-term goal is to lay the foundation for the design of safe, effective, and sufficiently specific inhibitors of disease-associated protein kinases.

项目摘要。蛋白激酶是人类细胞中普遍存在的信号传导酶的大家族。他们的 失调通常是癌症等疾病的基础，使其成为极好的治疗靶点。但 蛋白激酶催化结构域的高度结构和序列保守性使得 开发特异性抑制剂。许多临床上成功的激酶抑制剂部分通过以下方式实现特异性： 仅与不同的激酶构象结合。虽然分析了成千上万的X射线晶体结构， 蛋白激酶已经表明单个激酶结构域可以接近不同的活性和非活性构象， 关于激酶如何在构象之间相互转化知之甚少。这项建议的理由是， 定量了解这些构象的稳定性和它们相互转化的动力学， 了解健康和疾病状态下激酶活性、调节、配体结合和耐药性的关键。 这个项目的目标是获得构象动力学的作用的全面理解 通过改变药物解离速率来研究激酶功能、调节和耐药性。该提案是部分 围绕三个问题展开的一系列研究 Q1：调控结构域、相互作用蛋白和疾病相关突变如何影响构象 酪氨酸激酶的动力学我们的目标是确定Src激酶结构域的溶液动力学 对这些生物学上重要的扰动做出反应。 配体结合动力学的分子和细胞决定因素是什么？我们将测试我们的计算 通过评估药物亲和力，在体外和细胞中实验地建立药物结合过程的模型， 结合和解离动力学。我们的目标是确定药物结合过程的定量参数 以及这些参数的突变是如何导致耐药性的。 问题3：如何使用抑制数据的表型聚类来揭示隐藏的激酶特征？我们的目标是 挖掘激酶组范围的抑制数据集，根据其抑制表型对激酶进行分组，这反映了 进化压力和其他生物学功能对激酶的适应。 我们将使用结构方法（X射线和核磁共振），细胞药物结合和活性测定，配体结合 动力学、蛋白质工程、化学生物学和各种计算方法。生产网络 合作支持这个项目。该项目的影响是为临床医生提供 耐药突变，药物化学家与激酶抑制剂的药效学和药代动力学， 细胞生物学家用参数来理解激酶信号。长期目标是为 设计安全、有效和足够特异的疾病相关蛋白激酶抑制剂。