Functional Dynamics During Induced-fit Enzyme Turnover

越来越明显的是，动态运动可以与结构一样重要 生物分子作用机制。已经确定了7万种蛋白质的结构 在实验中，但只有少数人的动态得到了全面的映射。 核磁共振光谱学的新发展使在有利的情况下， 描述在一系列与功能相关的时间范围内的动态。精氨酸激酶 已经被开发为一个模型系统，服从于几种必要的技术，以 表征具有代表性的代谢酶的构象动力学。它将被用来 阐明催化反应中临界点的本征运动和底物诱导运动的相互作用 并了解蛋白质动力学如何限制酶的周转率。 精氨酸激酶(AK)是一种很有吸引力的模型酶，因为它催化磷酸化转移 反应具有受构象动力学限制的毫秒周转速率。它的体积为42 kDa 比以前表征的系统更大，并展示了丰富的结构域旋转曲目 和回旋运动。原子分辨率的晶体结构将与来自 几种类型的核磁共振建立跨越皮秒到皮秒的结构动力学模型 毫秒制度。AK是研究近天然蛋白质的绝佳机会 过渡态(TS)的动力学，因为它与TS类似，不同于双底物络合物 用于大多数双分子酶，不受人工共价限制。 目标1将我们的动力学特性从无底物酶扩展到过渡态 利用核磁共振弛豫色散、剩余偶极耦合和自旋自旋合成的模拟络合物 放松一下。这将揭示当酶在整个过程中进行时主干运动的变化 催化循环，以及快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。方法将支持整体集成 来自不同的结晶学和核磁共振实验的补充数据。目标3将决定 每一项动议的功能作用。反应酶核磁共振弛豫交换的变化 底物浓度将区分结合或解离所需的运动 那些在化学步骤中很重要的东西。 我们的实验分析将为当前关于诱导匹配作用的理论辩论提供信息， 蛋白质运动中的构象选择和过渡态稳定。它将决定 快慢动力学之间的联系程度，阐明了不同运动之间的协调 一个大的蛋白质，并揭示了酶如何在经历 大的构象变化。该项目将在基础生物化学和建筑领域产生广泛影响 了解疾病的分子基础的基础。

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.