A Combined DFT, Energy Decomposition, and Data Analysis Approach to Investigate the Relationship Between Noncovalent Interactions and Selectivity in a Flexible DABCOnium/Chiral Anion Catalyst System.
Edward MillerBinh Khanh MaiJacquelyne A ReadWilliam C BellJeffrey S DerrickPeng LiuF Dean TostePublished in: ACS catalysis (2022)
Developing strategies to study reactivity and selectivity in flexible catalyst systems has become an important topic of research. Herein, we report a combined experimental and computational study aimed at understanding the mechanistic role of an achiral DABCOnium cofactor in a regio- and enantiodivergent bromocyclization reaction. It was found that electron-deficient aryl substituents enable rigidified transition states via an anion- π interaction with the catalyst, which drives the selectivity of the reaction. In contrast, electron-rich aryl groups on the DABCOnium result in significantly more flexible transition states, where interactions between the catalyst and substrate are more important. An analysis of not only the lowest-energy transition state structures but also an ensemble of low-energy transition state conformers via energy decomposition analysis and machine learning was crucial to revealing the dominant noncovalent interactions responsible for observed changes in selectivity in this flexible system.
Keyphrases
- ionic liquid
- room temperature
- data analysis
- highly efficient
- reduced graphene oxide
- machine learning
- carbon dioxide
- metal organic framework
- structural basis
- visible light
- magnetic resonance
- solid state
- high resolution
- electron transfer
- deep learning
- gold nanoparticles
- artificial intelligence
- computed tomography
- molecular docking