Accelerated Discovery of Functional Tetramine-based Metal-Organic Cages using High-throughput Computational Screening Methods

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Metal-organic cages (MOCs) are tiny artificial containers in the shape of polyhedra built from organic linkers and metal-ions. Their ability to bind smaller molecules (guests) within their cavities gives them potential applicability in fields such as catalysis, separations, sensing, drug delivery and biotechnology. This work aims towards the development of new functional MOCs, prepared from tetramine linkers through subcomponent self-assembly. The conventional discovery process of such MOCs involves trial-and-error processes which can lead to a waste of time and resources. This project aims to accelerate this process by employing virtual screening methods based on the open-sourced python library stk56. This approach will lead to the selection of a set of building blocks that are suggested to self-assemble into new MOCs, for example with progressively larger cavity sizes or with anisotropic cavities. These building blocks will be prepared in the lab and their self- assembly and functionality will be investigated. This project is expected to provide insight into the fundamental design principles of MOCs and to lead to the discovery of MOCs with new functionality. Due to the interdisciplinary character, this project is expected to foster collaborations between researchers from a variety of fields such as supramolecular chemistry, computer science, computational chemistry, and mathematics.