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Divergence of catalytic systems in the zinc-catalysed alkylation of benzaldehyde mediated by chiral proline-based ligands

Abstract

Asymmetric catalysis has expanded the range of chiral products readily accessible through increasingly efficient synthetic catalysts. The development of these catalysts often starts with a result obtained by systematic screening of known privileged chiral structures and assumes that the active species would be an isolated monomolecular species. Here we report the study of three proline-derived ligands, diphenyl-N-methyl-prolinol, diphenylprolinol and 5-(hydroxydiphenylmethyl)-2-pyrrolidinone, in the zinc-catalysed alkylation of benzaldehyde. The three ligands exhibit different system-level behaviour, characterized by multiple levels of aggregation that may be catalytically active simultaneously. While diphenyl-N-methyl-prolinol behaves as expected from a mechanistic point of view, diphenylprolinol shows enantiodivergence during the reaction due to an asymmetric autoinduction process. With 5-(hydroxydiphenylmethyl)-2-pyrrolidinone, we were able to establish the possibility of at least trimeric active species in equilibrium with less aggregated active species. Simulations using a mathematical model confirm the possibility of such systems-level behaviour. Parallel study of the three systems reveals three distinct system-level behaviours that are central to the efficiency of the catalytic reaction.

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Fig. 1: General figure for the systems-level behaviour in asymmetric catalysis.
Fig. 2: Enantioselective addition of dialkylzinc to benzaldehyde catalysed by three chiral diphenylprolinol derivatives.
Fig. 3: DPMP-catalysed addition of ZnEt2 to benzaldehyde (0.15 M) at 20 °C in toluene as solvent.
Fig. 4: DPP (2)-catalysed addition of ZnEt2 to benzaldehyde (0.4 M) at 20 °C in toluene as solvent.
Fig. 5: DPPy (3)-catalysed addition of ZnEt2 to benzaldehyde (0.25 M) at 20 °C in toluene as solvent.
Fig. 6: Developed scheme of the monomer–dimer–trimer competition model.
Fig. 7: Simulations of NLE and e.e.P versus catalyst-loading curves.

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Data availability

The data that support the findings of this study are available in the Supporting Information. Source data are provided with this paper.

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Acknowledgements

This research was supported by the Interdisciplinary Thematic Institute ITI-CSC via the IdEx Unistra (ANR-10-IDEX-0002) within the programme Investissement d’Avenir (T.T.) and the Ministère de l’Enseignement Supérieur et de la Recherche (MESR) for a PhD grant to Y.G. We thank the NMR department of CNRS FR2010 Strasbourg and in particular B. Vincent for his valuable studies. We also thank T. Achard, A. Maisse-François and E. Couzigné from IPCMS Strasbourg.

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T.T. performed the synthetic experiments. Y.G. made the mathematical models and computed simulations. T.T., Y.G. and S.B.-L. performed the data analyses. S.B.-L. conceptualized and supervised the study, and wrote the manuscript with T.T. and Y.G.

Corresponding author

Correspondence to Stéphane Bellemin-Laponnaz.

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Nature Synthesis thanks Oliver Trapp and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Thomas West, in collaboration with the Nature Synthesis team.

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Supplementary information

Supplementary Information

All details of syntheses, experimental procedures and mathematical treatments.

Supplementary Data 1

Spreadsheet program for ML models (Supplementary Information, sections 3.3 and 3.4).

Supplementary Data 2

Numerical experimental data for Supplementary Fig. 1.

Supplementary Data 3

Numerical experimental data for Supplementary Fig. 2.

Supplementary Data 4

Numerical experimental data for Supplementary Fig. 3.

Supplementary Data 5

Numerical experimental data for Supplementary Fig. 4.

Supplementary Data 6

Numerical experimental data for Supplementary Fig. 5.

Supplementary Data 7

Numerical experimental data for Supplementary Fig. 6.

Supplementary Data 8

Numerical experimental data for Supplementary Fig. 7.

Supplementary Data 9

Numerical experimental data for Supplementary Fig. 8.

Supplementary Data 10

Numerical experimental data for Supplementary Fig. 9.

Supplementary Data 11

Numerical experimental data for Supplementary Fig. 10.

Supplementary Data 12

Numerical experimental data for Supplementary Fig. 11.

Supplementary Data 13

Numerical simulation data for Supplementary Fig. 12.

Supplementary Data 14

Numerical experimental data for Supplementary Fig. 13.

Supplementary Data 15

Numerical experimental data for Supplementary Fig. 14.

Supplementary Data 16

Numerical experimental data for Supplementary Fig. 15.

Supplementary Data 17

Numerical experimental data for Supplementary Fig. 16.

Supplementary Data 18

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Supplementary Data 19

Numerical simulation data for Supplementary Fig. 19.

Source data

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Numerical experimental data.

Source Data Fig. 4

Numerical experimental data.

Source Data Fig. 5

Numerical experimental data.

Source Data Fig. 7

Numerical simulation data.

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Thierry, T., Geiger, Y. & Bellemin-Laponnaz, S. Divergence of catalytic systems in the zinc-catalysed alkylation of benzaldehyde mediated by chiral proline-based ligands. Nat. Synth (2024). https://doi.org/10.1038/s44160-024-00491-y

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