Functional Dynamics During Induced-fit Enzyme Turnover

越来越明显的是，动态运动与结构同样重要， 生物分子作用机制。已经确定了7万种蛋白质的结构 实验上，但只有少数的动力学已经被全面绘制。 NMR光谱学的新兴发展使得在有利的情况下， 在广泛的功能相关的时间制度的动态特性。精氨酸激酶 已经发展成为一个模型系统，适用于几种必要的技术， 表征代表性代谢酶的构象动力学。它将用于 阐明在催化过程中的临界点处内在运动和底物诱导运动的相互作用。 循环，并了解蛋白质动力学如何限制酶周转率。 精氨酸激酶（AK）是一种有吸引力的模型酶，因为它催化磷酰基转移 反应的毫秒周转率是有限的构象动力学。在42 kDa处， 比以前表征的系统更大，并表现出丰富的域旋转库 和循环运动。原子分辨率的晶体结构将与来自 几种类型的核磁共振，以建立一个结构动态模型，跨越皮秒，通过 毫秒机制AK提供了一个研究近天然蛋白质的绝佳机会 过渡态（TS）的动力学，因为它的TS类似物，不像双底物复合物 用于大多数双分子酶，不受人工共价约束。 目标1将我们的动力学表征从无底物酶扩展到过渡态 模拟复合物，使用NMR弛豫色散，残余偶极耦合和自旋-自旋 放松.这将揭示随着酶通过膜的进展，主链运动的变化。 催化循环，以及快速和缓慢动力学的相互作用。Aim 2将开发计算机 结构动力学模型的优化算法。方法将支持整体整合 来自不同结晶学和核磁共振实验的互补数据。目标3将决定 每个动作的功能作用。反应酶NMR弛豫交换的变化 与底物浓度的关系将区分结合或解离所需的运动与 化学步骤中的重要步骤。 我们的实验分析将为当前关于诱导契合作用的理论争论提供信息， 蛋白质运动中的构象选择和过渡态稳定。它将决定 快速和慢速动力学之间的联系程度，阐明不同运动的协调， 一个大的蛋白质，并揭示酶如何实现精确的底物对齐，同时进行 大的构象变化。该项目将对基础生物化学产生广泛影响， 理解疾病分子基础的基础。

It is increasingly apparent that dynamic motions can be equally important as structure in biomolecular mechanisms of action. Structures of 70,000 proteins have been determined experimentally, but the dynamics of only a handful have been mapped comprehensively. Emerging developments in NMR spectroscopy are making it possible, in favorable cases, to characterize dynamics over a broad range of functionally-relevant time regimes. Arginine kinase has been developed as a model system, amenable to the several techniques necessary, to characterize the conformational dynamics of a representative metabolic enzyme. It will be used to elucidate the interplay of intrinsic and substrate-induced motions at critical points in the catalytic cycle and to understand how protein dynamics can limit enzymatic turnover rate. Arginine kinase (AK) is an attractive model enzyme because it catalyzes a phosphoryl transfer reaction with a millisecond turnover rate that is limited by conformational dynamics. At 42 kDa, it is larger than previously characterized systems and exhibits a rich repertoire of domain rotations and loop motions. Crystal structures at atomic resolution will be combined with dynamics from several types of NMR to build a structure-dynamic model spanning the pico-second through millisecond regimes. AK presents an excellent opportunity to investigate near-native protein dynamics of the transition state (TS), because its TS analog, unlike the bisubstrate complexes used for most bimolecular enzymes, is free from artificial covalent constraints. Aim 1 will extend our dynamics characterization from substrate-free enzyme to a transition state analog complexes, using NMR relaxation dispersion, residual dipolar coupling and spin-spin relaxation. This will reveal changes in backbone motions as the enzyme progresses through the catalytic cycle, and the interplay of fast and slow dynamics. Aim 2 will develop computer algorithms for optimization of structure-dynamics models. Methods will support holistic integration of complementary data from diverse crystallographic and NMR experiments. Aim 3 will determine the functional role of each motion. Variation in the NMR relaxation exchange of reacting enzyme with substrate concentration will distinguish motions required for binding or dissociation from those important in chemical steps. Our experimental analysis will inform current theoretical debate about the roles of induced-fit, conformational selection and transition state stabilization in protein motions. It will determine the extent of links between fast and slow dynamics, elucidate the coordination of different motions in a large protein, and reveal how enzymes achieve precise substrate alignment while undergoing large conformational changes. The project will have broad impact in basic biochemistry and build the foundations for understanding the molecular basis of disease.