Saa Pedro, Nielsen Lars K
Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Queensland, Australia.
PLoS Comput Biol. 2015 Apr 14;11(4):e1004195. doi: 10.1371/journal.pcbi.1004195. eCollection 2015 Apr.
Kinetic models provide the means to understand and predict the dynamic behaviour of enzymes upon different perturbations. Despite their obvious advantages, classical parameterizations require large amounts of data to fit their parameters. Particularly, enzymes displaying complex reaction and regulatory (allosteric) mechanisms require a great number of parameters and are therefore often represented by approximate formulae, thereby facilitating the fitting but ignoring many real kinetic behaviours. Here, we show that full exploration of the plausible kinetic space for any enzyme can be achieved using sampling strategies provided a thermodynamically feasible parameterization is used. To this end, we developed a General Reaction Assembly and Sampling Platform (GRASP) capable of consistently parameterizing and sampling accurate kinetic models using minimal reference data. The former integrates the generalized MWC model and the elementary reaction formalism. By formulating the appropriate thermodynamic constraints, our framework enables parameterization of any oligomeric enzyme kinetics without sacrificing complexity or using simplifying assumptions. This thermodynamically safe parameterization relies on the definition of a reference state upon which feasible parameter sets can be efficiently sampled. Uniform sampling of the kinetics space enabled dissecting enzyme catalysis and revealing the impact of thermodynamics on reaction kinetics. Our analysis distinguished three reaction elasticity regions for common biochemical reactions: a steep linear region (0> ΔGr >-2 kJ/mol), a transition region (-2> ΔGr >-20 kJ/mol) and a constant elasticity region (ΔGr <-20 kJ/mol). We also applied this framework to model more complex kinetic behaviours such as the monomeric cooperativity of the mammalian glucokinase and the ultrasensitive response of the phosphoenolpyruvate carboxylase of Escherichia coli. In both cases, our approach described appropriately not only the kinetic behaviour of these enzymes, but it also provided insights about the particular features underpinning the observed kinetics. Overall, this framework will enable systematic parameterization and sampling of enzymatic reactions.
动力学模型提供了理解和预测酶在不同扰动下动态行为的方法。尽管具有明显优势，但经典参数化需要大量数据来拟合其参数。特别是，表现出复杂反应和调节（变构）机制的酶需要大量参数，因此通常由近似公式表示，这便于拟合但忽略了许多实际的动力学行为。在这里，我们表明，只要使用热力学上可行的参数化，通过采样策略就可以实现对任何酶的合理动力学空间的全面探索。为此，我们开发了一个通用反应组装和采样平台（GRASP），它能够使用最少的参考数据对精确的动力学模型进行一致的参数化和采样。前者整合了广义MWC模型和基本反应形式。通过制定适当的热力学约束，我们的框架能够对任何寡聚酶动力学进行参数化，而不会牺牲复杂性或使用简化假设。这种热力学安全的参数化依赖于参考状态的定义，在此基础上可以有效地采样可行的参数集。动力学空间的均匀采样能够剖析酶催化作用，并揭示热力学对反应动力学的影响。我们的分析区分了常见生化反应的三个反应弹性区域：陡峭的线性区域（0>ΔGr>-2 kJ/mol）、过渡区域（-2>ΔGr>-20 kJ/mol）和恒定弹性区域（ΔGr<-20 kJ/mol）。我们还应用这个框架对更复杂的动力学行为进行建模，如哺乳动物葡萄糖激酶的单体协同性和大肠杆菌磷酸烯醇式丙酮酸羧化酶的超敏反应。在这两种情况下，我们的方法不仅恰当地描述了这些酶的动力学行为，还提供了关于支撑观察到的动力学的特定特征的见解。总体而言，这个框架将能够对酶促反应进行系统的参数化和采样。
