Issue 33, 2020

Synthetic and computational assessment of a chiral metal–organic framework catalyst for predictive asymmetric transformation

Abstract

Understanding and controlling molecular recognition mechanisms at a chiral solid interface is a continuously addressed challenge in heterogeneous catalysis. Here, the molecular recognition of a chiral peptide-functionalized metal–organic framework (MOF) catalyst towards a pro-chiral substrate is evaluated experimentally and in silico. The MIL-101 metal–organic framework is used as a macroligand for hosting a Noyori-type chiral ruthenium molecular catalyst, namely (benzene)Ru@MIL-101-NH-Gly-Pro. Its catalytic perfomance toward the asymmetric transfer hydrogenation (ATH) of acetophenone into R- and S-phenylethanol are assessed. The excellent match between the experimentally obtained enantiomeric excesses and the computational outcomes provides a robust atomic-level rationale for the observed product selectivities. The unprecedented role of the MOF in confining the molecular Ru-catalyst and in determining the access of the prochiral substrate to the active site is revealed in terms of highly face-specific host–guest interactions. The predicted surface-specific face differentiation of the prochiral substrate is experimentally corroborated since a three-fold increase in enantiomeric excess is obtained with the heterogeneous MOF-based catalyst when compared to its homogeneous molecular counterpart.

Graphical abstract: Synthetic and computational assessment of a chiral metal–organic framework catalyst for predictive asymmetric transformation

Supplementary files

Article information

Article type
Edge Article
Submitted
17 6月 2020
Accepted
05 8月 2020
First published
06 8月 2020
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2020,11, 8800-8808

Synthetic and computational assessment of a chiral metal–organic framework catalyst for predictive asymmetric transformation

J. Canivet, E. Bernoud, J. Bonnefoy, A. Legrand, T. K. Todorova, E. A. Quadrelli and C. Mellot-Draznieks, Chem. Sci., 2020, 11, 8800 DOI: 10.1039/D0SC03364B

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