Collaborative experimental & computational studies of conformational transitions

协作实验

• 批准号: 8811981
• 负责人: MICHAEL F HAGAN
• 金额: $ 30.61万
• 依托单位: BRANDEIS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8811981
• 关键词: Amino Acids; Behavior; Biological Assay; Biology; Biophysics; Catalysis; Cellular Structures; Complex; Computing Methodologies; Data; Dependence; Disease; Drug Design; Drug Targeting; Elements; Entropy; Environment; Enzymes; Escherichia coli; Family; Grant; Health; Homologous Gene; Homologous Protein; Individual; Kinetics; Knowledge; Lead; Light; Link; Measures; Methods; Modeling; Molecular; Molecular Conformation; Mutagenesis; Mutation; Nature; Organism; Pathway interactions; Performance; Point Mutation; Process; Protein Conformation; Proteins; Relaxation; Reporting; Resolution; Sampling; Series; Shapes; Signal Transduction; Signaling Protein; Structure; System; Temperature; Testing; Time; Water; adenylate kinase; base; computer studies; conformational conversion; design; enzyme activity; extreme temperature; flexibility; meetings; member; molecular dynamics; multidisciplinary; mutant; novel; pressure; protein folding; protein function; protein structure; research study; response; simulation

DESCRIPTION (provided by applicant): Protein conformational transitions are fundamental to signaling, enzyme catalysis, and assembly of cellular structures. Developing a quantitative understanding of how proteins interconvert between different folded structures is a grand challenge in biology; meeting this challenge would have an impact in treating a large number of diseases that are linked to signaling cascades or enzymes. This proposal aims to understand the physical principles that control protein conformational transitions by characterizing transitio pathways in proteins. Since these pathways are very complex, homologous proteins will be compared to make this aim feasible. We focus on a signaling proteins from the two-component system family (NtrC) and homologs of the enzyme adenylate kinase (Adk) from E. coli and extremophiles. These Adk homologs have optimal enzymatic activity at extreme temperature or pressure. An iterative approach between NMR dynamics experiments, advanced computational methods and functional assays is proposed. (1) Structures of stable conformational states and rates of interconversion between them are measured experimentally, (2) transition pathways are computationally characterized in atomistic detail, (3) crucial interactions that facilitate pathway are identified, (4) mutations are designed that disable these interactions, (5) the resulting changes in interconversion rates are measured experimentally, and (6) new computations are performed based on experimental observations. By comparing transition pathways among homologous proteins and mutants key residues are identified that lead to mechanistic differences, and confer their respective temperature or pressure behaviors. Furthermore, determining interconversion entropy and entropy changes for these enzymes adapted to extreme environments may shed light on the evolutionary selection mechanisms that shaped primitive enzymes. In a broader context, knowledge gained from the molecular pathways may elucidate general principles of conformational transitions in proteins, thereby expanding our understanding of protein energy landscapes from the ground states to "transition landscapes".

描述（由申请人提供）：蛋白质构象转变是信号传导，酶催化和组装细胞结构的基础。对蛋白质如何在不同折叠结构之间相互互换是生物学的巨大挑战。应对这一挑战将对与信号级联或酶有关的大量疾病产生影响。 该建议旨在通过表征蛋白质中的转运途径来理解控制蛋白质构象转变的物理原理。由于这些途径非常复杂，因此将比较同源蛋白，以使该目标可行。我们专注于来自两个组分系统家族（NTRC）的信号传导蛋白，以及来自大肠杆菌和极端细胞的酶腺苷酸激酶（ADK）的同源物。这些ADK同源物在极端温度或压力下具有最佳的酶活性。 提出了NMR动力学实验，高级计算方法和功能测定之间的迭代方法。 （1）通过实验测量稳定的构象状态和之间的相互转换速率，（2）过渡途径在计算中以原子式细节进行计算表征，（3）确定促进途径的关键相互作用，（4）突变被设计为禁用这些相互作用的相互作用；通过比较同源蛋白和突变体之间的过渡途径，可以确定关键残基导致机械差异，并赋予其各自的温度或压力行为。此外，确定适合极端环境的这些酶的互换熵和熵变化可能会阐明塑造原始酶的进化选择机制。在更广泛的背景下，从分子途径中获得的知识可以阐明蛋白质中构象过渡的一般原理，从而扩展我们对蛋白质能量景观从基础状态到“过渡景观”的理解。