Theoretical and Experimental Investigation of Chiral Separation by Crystallization

手性，即某些分子以具有相同物理性质的两个镜像（对映体）存在的能力，是生命的基本成分。在进化过程中，生物体选择只使用其中一个镜像来构建它们的手性分子；例如，所有生物体的氨基酸都具有相同的手性构型。这就解释了为什么引入生物体的药物的药理学或毒理学性质会因所使用的对映体而大不相同。不幸的是，这一点并不总是得到重视。沙利度胺悲剧中的出生缺陷仍然是对这一事实的悲伤提醒。难怪监管机构现在已经制定了严格的指导方针，以防止这种情况再次发生，而其他行业也变得越来越谨慎。例如，对映体纯杀虫剂比外消旋体杀虫剂（对映体混合物）更受欢迎，因为它们更有效，对环境的影响更小。我们对手性分子生物活性的更好理解导致了对映体纯化合物市场的空前增长。然而，尽管在合成化学方面取得了进步，但我们仍然距离大自然的完美还有很长的路要走，即利用酶来产生手性产物，而酶的作用是高度优化的，可以区分对映体。通常，化学合成的最终产物是外消旋混合物，需要通过合适的分离方法（如结晶）将其分解为其手性组分。不幸的是，从外消旋熔体或溶液中结晶很少导致自发分解（同手性晶体的机械混合物）。当这种情况不发生时，分离可以通过利用两个对映体与对映体纯溶解剂的不同相互作用来实现，形成一对具有不同物理性质的盐或分子配合物（非对映体）。通过明智地选择溶解剂，两种非对映体的溶解度将会有很大的不同，通过结晶出可溶性较低的那一种，它们的分离将成为可能。尽管这种方法被广泛使用，但解析剂和工艺条件的选择仍然是基于反复试验的。我们的研究旨在利用计算化学的进步和计算资源的可用性来解决预测如何通过结晶分离对映体的挑战。我们现在有高度精确的方法来模拟分子在原子水平上的相互作用。这将使我们能够从第一性原理上预测非对映体的晶体结构、热力学稳定性和性质，并进一步提高这些算法的准确性和可靠性。这些发展将导致对自发分解的理解和预测，以及当自发分解不发生时，对给定的外消旋混合物和分解剂的分解效率的理解和预测。然后，我们将能够通过改变其分子结构来设计溶解剂，以实现最佳分离，并随后优化工艺条件（例如温度）。不幸的是，开发和验证预测模型所需的全部实验数据，从晶体结构到分辨率效率，仅适用于少数系统。我们将使用化学，化学工程和分子建模的多学科能力来生成所需的实验数据以及计算建模。这项研究既及时又具有重要的工业意义，因为其结果将有助于减少消耗资源的试错实验，并满足开发专用化学产品的激进时间尺度。该项目的成功将降低生产成本，增加药品、食品和农用化学品的供应。

Chirality, the ability of some molecules to exist as two mirror images (enantiomers) with identical physical properties, is a basic ingredient of life. In the course of evolution, organisms opted to use just one of the mirror images for chiral molecules they are built from; for example amino acids of all living organisms have the same chiral configuration. This explains why the pharmacological or toxicological properties of drugs introduced to an organism can be very different depending on the enantiomer used. Unfortunately, this has not always been appreciated. Birth defects in the thalidomide tragedy still serve as a sad reminder of this fact. It is no wonder that regulatory authorities have now set strict guidelines to prevent this from happening again and other industries are becoming increasingly cautious. For example, enantiomerically pure insecticides are preferred over racemic ones (mixture of enantiomers) because they are more effective and have a smaller environmental impact.Our better understanding of the biological activity of chiral molecules has resulted in an unprecedented growth of the market for enantiomerically pure compounds. However, despite progress in synthetic chemistry, we are still far from the perfection of nature which produces chiral products by using enzymes whose action is highly optimised to discriminate between enantiomers. Frequently, the end product of a chemical synthesis is a racemic mixture which needs to be resolved into its chiral components via a suitable separation method, such as crystallisation. Unfortunately, crystallisation from a racemic melt or solution rarely leads to spontaneous resolution (mechanical mixture of homochiral crystals). When this does not occur, separation can be achieved by exploiting the fact that the two enantiomers interact differently with enantiomerically pure resolving agents, forming a pair of salts or molecular complexes (diastereomers) with different physical properties. By judiciously choosing the resolving agent, the solubility of the two diastereomers will be substantially different and their separation will be possible by crystallising out the less soluble one. Despite the widespread use of this method, the choice of the resolving agent and process conditions is still based on trial-and-error experimentation. Our research aims to exploit the progress of computational chemistry and increased availability of computing resources to address the challenge of predicting how to separate enantiomers by crystallisation. We now have highly accurate methods to model the interactions of molecules at the atomic level. This will allow us to predict the crystal structure, thermodynamic stability and properties of the diastereomers from first principles, and further advance the accuracy and reliability of these algorithms. These developments will lead to the understanding and prediction of spontaneous resolution and, when this does not occur, the resolution efficiency for a given racemic mixture and resolving agent. We will then be able to design resolving agents by altering their molecular structure to achieve the best possible separation and subsequently optimise the process conditions (e.g. temperature). Unfortunately, the full range of experimental data needed to develop and validate the predictive models, from crystal structures through to resolution efficiencies, are only available for a few systems. We will use multidisciplinary capabilities in chemistry, chemical engineering and molecular modelling to generate the required experimental data alongside computational modelling. The research is both timely and of significant industrial importance, as outcomes will help reduce resource-consuming trial-and-error experimentation, and meet the aggressive timescales for the development of specialised chemical products. Success in this project will result in reduced production costs and greater availability of drugs, food products and agrochemicals.