Towards Artificial Enzymes - Engineering a better-than-nature catalyst based on enzyme mimetics

酶是优良的生物催化剂，具有高度的选择性和特异性。它们可以促进特定反应在“绿色”条件下发生，潜在地减少工业化学合成对环境的负面影响。酶催化反应的多样性在不断增加，但尽管酶具有优异的催化活性，但酶只有在模拟生物世界的条件下才具有合理的效率：在pH中性的水条件下，温度适中。人工酶已成为有希望的候选者，因为它们在更广泛的条件下表现出比天然酶更好的稳定性。它们是基于一种已知酶的“最小催化单元”，尽管它们的体积很小，但它们提供了天然酶的基本优点。基于酶支架的系统的另一种选择是其他小分子，因为它们可以提供类似的工程物理化学环境。这样的系统并不局限于氨基酸官能团化学，而是可以用更复杂的功能部分阵列进行编程。动态组合化学（DCC）已成功地用于获得高效的催化剂，例如Diels-Alder反应。在DCC中，通过混合简单的构建块，在热力学控制下通过可逆反应（例如，二硫化物或亚胺交换）生成化合物混合物，从而产生动态组合库（DCL）。当DCL暴露于分子靶标时，与靶标结合的文库成员被稳定下来。这一原理允许人工催化剂的产生。在这种方法中，由DCL产生的组装在过渡态类似物（TSA）周围形成，随后将其移除以产生具有催化活性的分子大小的空腔。该项目旨在开发一种基于DCL（大环亚胺交换）的原理验证系统，该系统可以稳定在一系列酶催化反应中常见的异allox嗪-烟酰胺二元复合物-氧化还原对。这些系统催化氢化物从烟酰胺转移到黄素，并且可以很容易地通过瞬态吸收动力学进行跟踪。我们随后的目标是采用这种原理验证系统，并修改DCL优化架构，使其更“像酶一样”。即通过调整DCL组分的疏水性来提高TSA的熵稳定性。通过加入静电稳定剂，将进一步增强异丙嗪/烟酰胺氧化还原对的氧化还原电位。这将通过分子动力学模拟和基于结构的计算来研究。因此，第一个想法侧重于初始DCL的生成，并确定一个与异allox嗪-烟酰胺二元复合物形成稳定的主-客体复合物的组装结构。该项目还将涉及该结构的计算模拟，以便通过随后的化学功能化对人工催化剂进行基本调整。我们的目标是展示这种方法的潜力，为工业酶生物技术面临的许多挑战提供一种新的解决方案。我们还旨在提出可以进一步功能化不同类型化学或底物的架构。

Enzymes are excellent biological catalysts as they exhibit high selectivity and specificity. They can facilitate specific reactions to take place under "green" conditions, potentially reducing the negative impact played by the industrial chemical synthesis on the environment. The diverse range of enzyme catalysed reactions is continuously increasing, but despite their excellent catalytic activity, enzymes have reasonable efficiency only in conditions that mimic the biological world: moderate temperatures under pH neutral aqueous conditions. Artificial enzymes have emerged as promising candidates as they show improved stability over the natural ones under a wider variety of conditions. They are based on the "minimal catalytic unit" from a known enzyme, and, despite their small size, they provide the basic advantages of natural enzymes. An alternative to the systems based on enzyme scaffolds, is other small molecules as they could provide similar engineered physio-chemical environments. Such systems are not restricted to amino acid functional group chemistry, but instead can be programmed with a more complex array of functional moieties.Dynamic combinatorial chemistry (DCC) has been successfully used to obtain efficient catalysts, e.g. for the Diels-Alder reaction. In DCC, a mixture of compounds is generated via a reversible reaction under thermodynamic control (e.g., disulphide or imine exchange) by mixing simple building blocks, resulting in a dynamic combinatorial library (DCL). Upon exposure of a DCL to a molecular target, those library members that bind to the target are stabilised. This principle allows the generation of artificial catalysts. In this approach, the assembly arising from the DCL is formed around a transition state analogue (TSA), that is subsequently removed to generate catalytically active molecular-sized cavities. The project aims to develop a proof-of-principle system based on a DCL (macrocycle imine exchange) that stabilises an isoalloxazine-nicotinamide binary complex - redox couple commonly found in a range of enzyme catalysed reactions. These systems catalyse hydride transfer from the nicotinamide to the flavin, and can be easily tracked by transient absorption kinetics. We subsequently aim to take this proof-of-principle system and modify the DCL optimised architecture to be more "enzyme-like". That is, tuning the hydrophobicity of the DCL components to achieve improved entropic stabilisation of the TSA. By incorporating electrostatic stabilisation will further enhance the redox potential of the isoalloxazine / nicotinamide redox couple. This will be investigated by molecular dynamics simulations and structure based calculations.The first idea thus focuses on the generation of the initial DCL and identify an assembly architecture that forms a stable host-guest complex with the isoalloxazine-nicotinamide binary complex. The project will also involve computational simulations of this architecture to enable rationale tuning of the artificial catalyst through subsequent chemical functionalisation. We aim to demonstrate the potential of this approach for providing a novel solution to many of the challenges faced in industrial enzyme biotechnology. We also aim to suggest architectures that can be further functionalised for different types of chemistry or substrates.