School of Science, University of Waikato, Hamilton 3240, New Zealand; email:
Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom; email:
Annu Rev Biophys. 2020 May 6;49:163-180. doi: 10.1146/annurev-biophys-121219-081520. Epub 2020 Feb 4.
We review the adaptations of enzyme activity to different temperatures. Psychrophilic (cold-adapted) enzymes show significantly different activation parameters (lower activation enthalpies and entropies) from their mesophilic counterparts. Furthermore, there is increasing evidence that the temperature dependence of many enzyme-catalyzed reactions is more complex than is widely believed. Many enzymes show curvature in plots of activity versus temperature that is not accounted for by denaturation or unfolding. This is explained by macromolecular rate theory: A negative activation heat capacity for the rate-limiting chemical step leads directly to predictions of temperature optima; both entropy and enthalpy are temperature dependent. Fluctuations in the transition state ensemble are reduced compared to the ground state. We show how investigations combining experiment with molecular simulation are revealing fundamental details of enzyme thermoadaptation that are relevant for understanding aspects of enzyme evolution. Simulations can calculate relevant thermodynamic properties (such as activation enthalpies, entropies, and heat capacities) and reveal the molecular mechanisms underlying experimentally observed behavior.
我们回顾了酶活性对不同温度的适应。与中温适应酶相比,嗜冷(适应低温)酶的活化参数(较低的活化焓和熵)有显著差异。此外,越来越多的证据表明,许多酶催化反应的温度依赖性比人们普遍认为的要复杂得多。许多酶的活性与温度的关系图显示出曲线,这不能用变性或展开来解释。这可以用大分子速率理论来解释:限速化学步骤的负活化热容量直接导致对温度最优值的预测;熵和焓都是温度依赖的。与基态相比,过渡态集合中的波动减少。我们展示了如何将实验与分子模拟相结合,揭示与理解酶进化方面相关的酶热适应的基本细节。模拟可以计算相关的热力学性质(如活化焓、熵和热容),并揭示实验观察到的行为背后的分子机制。