Department of Chemistry, Molecular Sciences Research Hub, Imperial College London, White City Campus, Wood Lane, London, W12 0BZ, UK.
Chem Commun (Camb). 2022 Mar 18;58(23):3717-3730. doi: 10.1039/d2cc00532h.
Metal-organic cages are macrocyclic structures that can possess an intrinsic void that can hold molecules for encapsulation, adsorption, sensing, and catalysis applications. As metal-organic cages may be comprised from nearly any combination of organic and metal-containing components, cages can form with diverse shapes and sizes, allowing for tuning toward targeted properties. Therefore, their near-infinite design space is almost impossible to explore through experimentation alone and computational design can play a crucial role in exploring new systems. Although high-throughput computational design and screening workflows have long been known as powerful tools in drug and materials discovery, their application in exploring metal-organic cages is more recent. We show examples of structure prediction and host-guest/catalytic property evaluation of metal-organic cages. These examples are facilitated by advances in methods that handle metal-containing systems with improved accuracy and are the beginning of the development of automated cage design workflows. We finally outline a scope for how high-throughput computational methods can assist and drive experimental decisions as the field pushes toward functional and complex metal-organic cages. In particular, we highlight the importance of considering realistic, flexible systems.
金属-有机笼是一种大环结构，其内部具有固有空隙，可以容纳分子进行封装、吸附、传感和催化应用。由于金属-有机笼可以由几乎任何有机和含金属成分的组合制成，因此笼可以具有不同的形状和大小，从而可以针对目标性质进行调整。因此，它们几乎无限的设计空间仅通过实验探索是不可能的，而计算设计可以在探索新系统方面发挥关键作用。尽管高通量计算设计和筛选工作流程长期以来一直被认为是药物和材料发现的有力工具，但它们在探索金属-有机笼方面的应用更为最近。我们展示了金属-有机笼的结构预测和主客体/催化性能评估的示例。这些示例得益于处理含金属系统的方法的改进，这些方法具有更高的准确性，并且是自动化笼设计工作流程发展的开始。最后，我们概述了高通量计算方法如何在该领域朝着功能和复杂的金属-有机笼方向发展时，协助和推动实验决策的范围。特别地，我们强调了考虑现实、灵活系统的重要性。
