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Remote stereocontrol with azaarenes via enzymatic hydrogen atom transfer

Nature Chemistry volume 16, pages 277–284 (2024)Cite this article

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Abstract

Strategies for achieving asymmetric catalysis with azaarenes have traditionally fallen short of accomplishing remote stereocontrol, which would greatly enhance accessibility to distinct azaarenes with remote chiral centres. The primary obstacle to achieving superior enantioselectivity for remote stereocontrol has been the inherent rigidity of the azaarene ring structure. Here we introduce an ene-reductase system capable of modulating the enantioselectivity of remote carbon-centred radicals on azaarenes through a mechanism of chiral hydrogen atom transfer. This photoenzymatic process effectively directs prochiral radical centres located more than six chemical bonds, or over 6 Å, from the nitrogen atom in azaarenes, thereby enabling the production of a broad array of azaarenes possessing a remote γ-stereocentre. Results from our integrated computational and experimental investigations underscore that the hydrogen bonding and steric effects of key amino acid residues are important for achieving such high stereoselectivities.

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Fig. 1: Challenges and strategies for remote stereocontrol with an azaarene.
Fig. 2: Scope of azaarenes and alkenes in the enantioselective radical hydroalkylation reaction.
Fig. 3: Detailed insights into mechanistic studies of OYE1.
Fig. 4: Insights from computational analyses of enzyme mechanisms.

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Data availability

Data relating to the materials and methods, optimization studies, experimental procedures, calculations, atomic coordinates, high-performance liquid chromatography spectra and nuclear magnetic resonance spectra are available in Supplementary Information and supplementary data. The structure of OYE1 used for our calculations is available in the PDB database (3TX9). All data are available from the corresponding author upon reasonable request.

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Acknowledgements

This work was funded by the DOE Center for Advanced Bioenergy and Bioproducts Innovation, under the auspices of the US Department of Energy, Office of Science, Office of Biological and Environmental Research (award number DE-SC0018420 to H.Z.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We acknowledge the Computational Chemistry Commune (http://bbs.keinsci.com/) for their support with DFT calculations. Our research benefitted from the computing resources at Delta, the National Center for Supercomputing Applications, enabled by allocation BIO230016 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) programme, funded by National Science Foundation grants 2138259, 2138286, 2138307, 2137603 and 2138296. The Delta research computing initiative, funded by the National Science Foundation (award OCI 2005572), the State of Illinois, and a partnership between the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications, is deeply appreciated. We are indebted to G. Jiang and H. Cui for their invaluable insights. Special thanks to L. T. Burrus and M. C. O’Dell for their organizational assistance during the project.

Author information

Authors and Affiliations

  1. DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Maolin Li, Wesley Harrison, Zhengyi Zhang, Yujie Yuan & Huimin Zhao

  2. Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Maolin Li, Wesley Harrison, Zhengyi Zhang, Yujie Yuan & Huimin Zhao

  3. Carl Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Maolin Li, Wesley Harrison, Zhengyi Zhang, Yujie Yuan & Huimin Zhao

  4. NSF Molecular Maker Lab Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Huimin Zhao

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Contributions

The project was coordinated by H.Z., while H.Z. and M.L. jointly conceptualized the project and designed the research experiments. M.L. executed the experiments and computational studies. W.H. and Z.Z. were responsible for synthesizing some substrates, and Y.Y. contributed to the construction of the mutants.

Corresponding author

Correspondence to Huimin Zhao.

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Nature Chemistry thanks Debabrata Maiti and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Control experiments to evaluate reaction conditions.

Reaction conditions: α-methyl styrene (8 μmol), 2-bromomethyl pyridines (4 μmol), OYE1 (1 mol % based on α-methyl styrene), GDH-105 (5 U/mL), NADP+ (1 mol% based on glucose), glucose (20 μmol), 40 μL DMSO as additives in 1 ml (total) sodium acetate buffer, 445 nm LED, 25 °C, 12 h. The yields were determined by GC-MS. The ee values were determined by HPLC.

Extended Data Fig. 2 Implementation of Quantum Chemical Cluster Approach in OYE1 Protein.

The depicted model excludes the initial substrate. Calculations were executed employing the m062x-D3/def2tzvpp (SMD, ε = 4.0) // b3lyp-D3(BJ)/def2svp (gas) computational level. During the process of geometry optimization, fixed atoms are marked with an asterisk (‘*’). Visual representations were constructed with Pymol (Version 2.5.5) and CLYview 1.0b.

Extended Data Fig. 3 Comprehensive spin density analysis covering intermediates and HAT transition states.

Utilizing Multiwfn 3.8 software, we conducted an in-depth spin density analysis. Visual representations were constructed with VMD (Version 1.9.3). The green and blue areas depict α and β spin respectively, with all amino acid residues (except N194) being omitted to ensure clarity in presentation.

Extended Data Fig. 4 In-depth experimental assessment of steric hindrance in key residues and topographic analysis.

The figure delves into the steric hindrance presented by key residues, particularly focusing on Y375A and T37A. A comprehensive topographic steric map is also provided, with %VBuried indicating the buried volume.

Supplementary information

Supplementary Information

Supplementary Methods, Figs. 1–9, Tables 1–7 and References.

Reporting Summary

Supplementary Data 1

Computational data for Cartesian coordinates of optimized structures.

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Li, M., Harrison, W., Zhang, Z. et al. Remote stereocontrol with azaarenes via enzymatic hydrogen atom transfer. Nat. Chem. 16, 277–284 (2024). https://doi.org/10.1038/s41557-023-01368-x

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