21BBSRC-NSF/BIO - Evolving quantum mechanical tunnelling in enzymes

氢化物、氢原子或质子转移的h转移反应在酶催化反应中普遍存在。现在已经确定，这些反应可以通过涉及某种程度的量子力学隧穿（QMT）的机制发生，因此是量子生物学的一个特征。QMT的贡献是高度可变的，一个悬而未决的问题仍然是，在酶催化过程中是否存在选择QMT的进化压力。从理论上讲，通过增加隧穿贡献来提高酶催化h转移反应的速率是可能的，因此这可以提供适应度优势。然而，增加隧穿贡献的典型策略也可能增加经典（过障）h转移的速率。在本提案中，我们的目标是将酶催化反应中的h隧穿实验研究与定向（实验室）进化（DE）和计算化学相结合。我们将平行研究两种不相关的酶：(i)乙醇脱氢酶（ADH）是一种被充分研究的氢化物隧道模型和工业生物催化酶。（ii） mbase是我们最近通过de开发的一种全新的森田-贝利斯-希尔曼酶。de将使用高通量和中等通量筛选方法进行筛选，选择与质子化和氘化底物（因此发生H-或D-转移）的活性，以便允许平行进化专为H-和D-转移而进化的酶。选择的变体将使用额外的动力学方法（停止流动的预稳态速率常数和动力学同位素效应，以及温度依赖性）进行实验表征，并通过x射线晶体学来解决可能的结构。这些选择的变体也将使用计算化学进行研究，这将允许确定QMT的贡献。这种方法将为探索酶进化过程中H-和D-转移动力学与QMT之间的关系提供一种新的、更全面的方法，并将确定选择改进的D-转移动力学是否为提高酶的性能提供了新的途径。我们将利用我们最近在将计算QMT贡献与实验动力学同位素效应（H-和d -转移动力学的比率）相关联，发展mbase和开发表征酶催化反应化学的自由能QM/MM计算方法方面的突破。据我们所知，这是第一次尝试使用DE来探测酶中的QMT，或者在DE实验中使用氘动力学作为选择。最近的一篇论文表明，实验室进化出的一种用于短链酸氘化的酶得到了改进，但选择是对protium而不是氘进行的。因此，该项目既及时又新颖，将为QMT在h转移酶进化过程中的作用提供新的见解。此外，由于药物选择性氘化的有效途径目前是一个热门话题，而且许多工业上重要的酶催化h转移，该方法也有望为合成和工业生物催化应用中的酶优化提供新的途径。

H-transfer reactions involving hydride, hydrogen atom or proton transfers are ubiquitous in enzyme-catalysed reactions. It is now well established that these reactions can occur via a mechanism involving some degree of quantum mechanical tunnelling (QMT), and thus are a feature of quantum biology. The QMT contribution is highly variable and an open question remains whether there has been evolutionary pressure to select for QMT during enzyme catalysis. Theoretically, it is possible to increase the rate of an enzyme-catalysed H-transfer reaction by increasing the tunnelling contribution, so this could offer a fitness advantage. However, typical strategies to increase the tunnelling contribution are also likely to increase the rate of classical (over-the-barrier) H-transfer. In this proposal we aim to combine experimental studies of H-tunnelling in enzyme catalysed reactions with directed (laboratory) evolution (DE) and computational chemistry. We will study two unrelated enzymes in parallel: (i), alcohol dehydrogenase (ADH) is a well-studied model hydride-tunnelling and industrial biocatalysis enzyme.(ii), MBHase is a de novo Morita-Baylis-Hillman enzyme, that we have recently developed through DE.DE will be performed using high- and medium-throughput screening methods that select for activity with both protiated and deuterated substrates (so either H- or D- transfer occurs) in order to allow parallel evolution of enzymes evolved specifically for H- and D- transfer. Selected variants will be experimentally characterised using additional kinetics methods (stopped-flow pre-steady state rate constants and kinetics isotope effects, and temperature dependencies) and by X-ray crystallography to solve structures where possible. These selected variants will also be investigated using computational chemistry, which will allow the QMT contribution to be determined. This approach will allow a new and more comprehensive approach to the exploration of the relationships between H- and D- transfer kinetics and QMT during enzyme evolution, and will establish whether selecting for improved D-transfer kinetics provides new avenues for improving enzyme performance.We will take advantage of our recent breakthroughs in correlating computed QMT contributions with experimental kinetics isotope effects (ratio of H- and D-transfer kinetics), in evolving MBHase and in the development of the free energy QM/MM computational methods of characterising enzyme-catalysed reaction chemistry. To the best of our knowledge, this is the first attempt at using DE to probe QMT in enzymes, or to use deuterium kinetics as selection during DE experiments. A recent paper showed improvement in a laboratory evolved enzyme for deuteration of short chain acids, but selection was performed with protium, not deuterium. The project is thus both timely and novel and will provide new insight into the role of QMT during evolution of H-transfer enzymes. Further, as efficient routes to selective deuteration of pharmaceuticals is currently a hot topic, and many industrially-important enzymes catalyse H-transfers, the methodology also promises to lead to a new approach to enzyme optimisation for applications in synthesis and industrial biocatalysis.