Combined experimental and computational investigations of a nucleophilic displacement reaction with a hydride leaving group

所有的生物--生命本身--都依赖于酶。酶是大的、天然的分子，可以使特定的生化反应快速发生，也就是说，酶是天然的催化剂。它们是非常好的催化剂，但到目前为止我们还不知道是什么让它们成为如此优秀的天然化学家。我们需要知道酶中的化学反应是如何发生的，这是单靠实验很难做到的。研究酶及其催化的反应有很多原因：许多药物是酶抑制剂(它们阻止特定的酶发挥作用)，因此对酶的更好理解将有助于新药的设计。更好地了解个别酶也应该有助于了解和预测遗传变异的影响，例如，在理解为什么有些人可能从特定的药物中受益，或可能面临疾病的风险。酶也是非常好的和环保的催化剂--了解它们的功能应该有助于设计和开发用于法医、合成、分析和生物技术应用的新的“绿色”催化剂。在新兴的纳米技术领域，酶也显示出作为“分子机器”的巨大前景。我们将开展一个合作项目，将实验生物化学与先进的计算机建模方法结合起来，详细分析一种非凡的酶是如何工作的。这种酶催化了一种不同寻常的反应，并被用于工业应用，但可以通过提高它的效率来改进它，我们希望通过设计改变它来做到这一点。我们将通过建模来预测酶(突变)变化的影响，并通过实验测试我们的预测。我们将开发和应用新的高级建模方法，能够准确地处理这些大型和复杂的系统及其催化的化学反应。同时进行实验和建模将有助于开发方法，通过测试它们的预测，还将有助于解释生化结果和计划新的实验(例如设计改变的酶)。我们将专注于亚磷酸脱氢酶，这是一种催化一种化学上独特的反应的酶，到目前为止还没有详细的机制了解。目前的计算机建模方法对研究酶反应的某些方面很有用--它们提供了制作酶如何工作的分子“电影”的独特潜力--但有重要的局限性。例如，酶的体积很大，需要密集的计算，这意味着目前的计算通常限于近似的计算方法，而且往往不可靠。对酶催化机制的可靠预测需要更准确的技术。我们将把以前在小分子化学反应研究中得到验证的高水平方法扩展到研究酶的反应。我们将开发新的混合方法，能够很好地描述化学键的断裂和形成的能量，并分析酶的动力学如何影响反应。这项工作将与实验研究合作进行。实验数据将是计算的基本输入。我们将对同一种酶进行预测和实验比较，以检验我们的理论方法，使用分子模型来分析和解释实验数据，并检验关于酶反应机理的假设。这种合作将涉及我们实验室之间方法、数据、想法和研究人员的转移和交换。我们开发的新方法将被广泛使用，对生物学家、生物化学家和其他从事生物催化工作的研究人员应该非常有用。

All of biology - life itself - depends on enzymes. Enzymes are large, natural molecules that allow specific biochemical reactions to take place quickly, that is to say enzymes are natural catalysts. They are very good catalysts, but as yet we do not understand what it is that makes them such good natural chemists. We need to know how chemical reactions happen in enzymes, something that is very difficult to do by experiments alone. There are many reasons for studying enzymes and the reactions they catalyse: many drugs are enzyme inhibitors (they stop specific enzymes from working), so better understanding of enzymes will help in the design of new drugs. Better understanding of individual enzymes should also help understand and predict the effects of genetic variation, for example in understanding why some people may benefit from a particular drug, or may be at risk from a disease. Enzymes are also very good and environmentally friendly catalysts - knowing how they function should help in the design and development of new 'green' catalysts for forensic, synthetic, analytical and biotechnological applications. Enzymes also show great promise as 'molecular machines' in the emerging field of nanotechnology. We will carry out a collaborative project bringing together experimental biochemistry with advanced computer modelling methods to analyse in detail how a remarkable enzyme works. This enzyme catalyses an unusual reaction, and is used in industrial applications, but it could be improved by making it more efficient, which we hope to do by designing changes to it. We will predict the effects of changes to the enzyme (mutations) by modelling, and test our predictions experimentally. We will develop and apply new high-level modelling methods, capable of dealing accurately with these large and complex systems, and the chemical reactions they catalyse. Carrying out experiments and modelling together will help develop the methods, by testing them predictions, and will also help in interpreting biochemical results and planning new experiments (e.g. designing altered enzymes). We will focus on phosphite dehydrogenase, an enzyme that catalyses a chemically unique reaction that so far has eluded detailed mechanistic understanding. Current computer modelling methods are useful for studying some aspects of enzyme reactions - they offer the unique potential of making molecular 'movies' of how enzymes work - but have important limitations. For example, large size of enzymes, and the need for intensive calculations, means that current calculations are typically limited to approximate and often unreliable computational methods. Reliable predictions of enzyme catalytic mechanisms require more accurate techniques. We will extend high-level methods, previously validated in studies of chemical reactions of small molecules, to study reactions in enzymes. We will develop new, hybrid methods that can describe the energies of breaking and forming chemical bonds well, and analyse how the reaction is affected by the dynamics of the enzyme. This work will be carried out in collaboration with experimental studies. The experimental data will be essential input for the calculations. We will make predictions and compare with experiments on the same enzyme to test our theoretical methods, use molecular models to analyse and interpret experimental data and test hypotheses about the enzyme reaction mechanism. This collaboration will involve the transfer and exchange of methods, data, ideas and researchers between our labs. The new methods we develop will be made widely available, and should be very useful to biologists, biochemists and other researchers working on biological catalysis.