Computational Modeling of Supramolecular Metallo-organic Cages-Challenges and Opportunities

Tomasz K. Piskorz, Vicente Martí-Centelles, Tom A. Young, Paul J. Lusby, Fernanda Duarte*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract / Description of output

Self-assembled metallo-organic cages have emerged as promising biomimetic platforms that can encapsulate whole substrates akin to an enzyme active site. Extensive experimental work has enabled access to a variety of structures, with a few notable examples showing catalytic behavior. However, computational investigations of metallo-organic cages are scarce, not least due to the challenges associated with their modeling and the lack of accurate and efficient protocols to evaluate these systems. In this review, we discuss key molecular principles governing the design of functional metallo-organic cages, from the assembly of building blocks through binding and catalysis. For each of these processes, computational protocols will be reviewed, considering their inherent strengths and weaknesses. We will demonstrate that while each approach may have its own specific pitfalls, they can be a powerful tool for rationalizing experimental observables and to guide synthetic efforts. To illustrate this point, we present several examples where modeling has helped to elucidate fundamental principles behind molecular recognition and reactivity. We highlight the importance of combining computational and experimental efforts to speed up supramolecular catalyst design while reducing time and resources.

Original languageEnglish
Pages (from-to)5806-5826
Number of pages21
JournalACS Catalysis
Issue number10
Early online date2 May 2022
Publication statusPublished - 20 May 2022

Keywords / Materials (for Non-textual outputs)

  • biomimetic catalysis
  • computational modeling
  • metallo-organic cages
  • supramolecular chemistry


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