Issue 23, 2022

Unlocking the computational design of metal–organic cages


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.

Graphical abstract: Unlocking the computational design of metal–organic cages

Article information

Article type
Feature Article
26 Jan 2022
22 Feb 2022
First published
25 Feb 2022
This article is Open Access
Creative Commons BY license

Chem. Commun., 2022,58, 3717-3730

Unlocking the computational design of metal–organic cages

A. Tarzia and K. E. Jelfs, Chem. Commun., 2022, 58, 3717 DOI: 10.1039/D2CC00532H

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