cgbind: A Python Module and Web App for Automated Metallocage Construction and Host-Guest Characterization

24 April 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


Metallocages offer a diverse and underexplored region of chemical space to search for novel catalysts and substrate hosts. However, the ability to tailor such structures towards applications in binding and catalysis is a challenging task. Here, we present an open-source computational toolkit, cgbind, that facilitates the characterization and prediction of functional metallocages. It employs known structural scaffolds as starting points, and computationally efficient approaches for the evaluation of geometric and chemical properties. To illustrate the applicability of cgbind, we evaluate the likelihood of 102 substrates to bind within M2L4 and M4L6 cages and achieve accuracy comparable or better than semi-empirical electronic structure methods. The cgbind code presented here is freely available at and also via a web-based graphical user interface at The protocol described here paves the way for high-throughput virtual screening of potential supramolecular structures, accelerating the search for new hosts and catalysts.


Supramolecular metallocages
Computational modelling

Supplementary materials

SI cgbind v1

Supplementary weblinks


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