Functional Dynamics and Activation Mechanisms in Enzymes

酶的功能动力学和激活机制

• 批准号: RGPIN-2019-04367
• 负责人: Prosser, Robert
• 金额: $ 3.5万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=748362
• 关键词: Functional; Dynamics; Activation; Mechanisms; Enzymes

Enzymes sample states primed to bind substrates, form Michaelis intermediates, adopt conformers facilitating chemical steps, & acquire states enabling product release, while minimizing the reverse process. Catalysis is enabled by a dynamic equilibrium of functional states, referred to as the ensemble. NMR goes beyond crystallography to capture high-resolution structures of ground & excited states in addition to both fast (local) & slow (cooperative) dynamics enabling catalysis. The ensemble perspective is both profoundly important to advancing our understanding of protein function & profoundly challenging, since we seek to describe all conformers with atomic resolution along the entire reaction coordinate pathway. While many enzymes could be studied, we focus on fluoroacetate dehalogenase (FAcD) as a model enzyme namely because it is a homodimer (the most common motif among proteins) thus inviting questions regarding intra- and intermolecular allostery, which is at the heart of protein function & least understood.  FacD also detoxifies a fluorinated poison & represents an interesting model to pursue mutagenesis, functional evolution, & bioremediation.  We will address: 1. The dynamic equilibrium of functional states. We will identify key functional states, determine the ensemble free energy landscape with a focus on interstate dynamics & solve a structure of at least one excited state (poised for substrate capture) for which there is no crystal structure. 2. Allosteric networks & mechanisms. Methyl (TROSY) & 19F NMR will provide a network of chemical shifts across the dimer. Covariance analysis of chemical shifts as a function of inhibitor, substrate analogue, & D2O will generate an allosteric network & address the critical role of hydrogen-bonded waters as allosteric switches. 3. Enzyme dynamics & catalysis. Dynamics will be assessed across the dimer via backbone & side chain relaxation experiments. We will study the connection between catalytic efficiency & molecular dynamics. 4. Substrate inhibition. We will study how an allosteric substrate pocket in the dimer contributes to inhibition at high concentrations & efficient catalysis at low concentrations. 5. 19F NMR assignments crystallography. We will improve the use of DFT & local MD simulations as an alternative to mutagenesis for 19F NMR assignments. 6. Protein folding of a dimer. Both denaturant & pressure will be used to study the complex folding process of this dimer with atomic resolution. 7. Protein mutagenesis & evolution. High numbers of variants will be made & studied via single cell (FACS) methods. Allosteric networks will be tested & the enzyme will be evolved toward greater catalytic efficiency or substrate promiscuity. Results will greatly advance understanding of the role of structure & dynamics in catalysis from the perspective of an ensemble, while addressing several paradigm shifting questions regarding allostery & water networks in a prototypical dimer.

酶样品状态引发结合底物，形成米氏中间体，采用构象促进化学步骤，并获得使产品释放的状态，同时最大限度地减少反向过程。催化是通过功能状态的动态平衡来实现的，称为系综。NMR超越了晶体学，除了快速（局部）和缓慢（合作）动力学实现催化之外，还可以捕获基态和激发态的高分辨率结构。系综的观点是非常重要的，以推进我们的蛋白质功能的理解和深刻的挑战，因为我们试图描述所有构象与原子分辨率沿着整个反应坐标途径。虽然许多酶可以被研究，但我们专注于氟乙酸脱卤酶（FAcD）作为模型酶，即因为它是同源二聚体（蛋白质中最常见的基序），因此引发了关于分子内和分子间变构的问题，这是蛋白质功能的核心&最不了解。FacD还解毒氟化毒素&代表了一个有趣的模型来追求诱变，功能进化，&生物修复。我们将解决：1.功能状态的动态平衡。我们将确定关键的功能状态，确定系综自由能景观，重点是状态间动力学和解决至少一个激发态的结构（准备基板捕获），其中没有晶体结构。 2.变构网络和机制。甲基（TROSY）和19F NMR将提供跨二聚体的化学位移网络。协方差分析的化学位移作为一个功能的抑制剂，底物类似物，和D2O将产生一个变构网络和地址的氢键沃茨作为变构开关的关键作用。 3.酶动力学和催化。将通过主链和侧链松弛实验评估整个二聚体的动力学。我们将研究催化效率和分子动力学之间的联系。 4.底物抑制。我们将研究二聚体中的变构底物口袋如何有助于高浓度下的抑制和低浓度下的有效催化。 5. 19F NMR分配结晶学。我们将改进DFT和局部MD模拟的使用，作为19F NMR分配诱变的替代方法。6.二聚体的蛋白质折叠。同时使用变性剂和压力，以原子级的分辨率来研究这种二聚体的复杂折叠过程。 7.蛋白质突变与进化。将通过单细胞（FACS）方法制备和研究大量变体。将测试变构网络&酶将朝着更高的催化效率或底物混杂的方向进化。 结果将大大推进理解的结构和动力学在催化的作用，从合奏的角度来看，同时解决几个范式转变的问题，关于变构和水网络在一个原型二聚体。