Abstract

The development of computational tools to support organic synthesis, including the prediction of reaction pathways, optimization and selectivity, is a topic of intense current interest. Transition state force fields, derived by the quantum-guided molecular mechanics method, rapidly calculate the stereoselectivity of organic reactions accurately enough to allow predictive virtual screening. Here we describe CatVS, an automated tool for the virtual screening of substrate and ligand libraries for asymmetric catalysis within hours. It is shown for the OsO4-catalysed cis-dihydroxylation that the results from the automated set-up are indistinguishable from a manual substrate screen. Predictive computational ligand selection is demonstrated in the virtual ligand screen of a library of diphosphine ligands for the rhodium-catalysed asymmetric hydrogenation of enamides. Subsequent experimental testing verified that the most selective substrate–ligand combinations are successfully identified by the virtual screen. CatVS is therefore a promising tool to increase the efficiency of high-throughput experimentation.

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Acknowledgements

This work was supported financially by NSF (CHE-1565669), NIH (T32 GM075762 and 1R01GM111645) and AstraZeneca. S. Tomasi, D. Buttar, and J. Westin at AstraZeneca are acknowledged for help with the CatVS web implementation.

Author information

Author notes

  1. These authors contributed equally: Anthony R. Rosales and Jessica Wahlers.

Affiliations

  1. Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, USA

    • Anthony R. Rosales
    • , Jessica Wahlers
    • , Eric Hansen
    • , Paul Helquist
    • , Olaf Wiest
    •  & Per-Ola Norrby
  2. Early Product Development, Pharmaceutical Sciences, IMED Biotech Unit, AstraZeneca Gothenburg, Mölndal, Sweden

    • Elaine Limé
    •  & Per-Ola Norrby
  3. Pharmaceutical Technology and Development, AstraZeneca, Silk Road Business Park, Macclesfield, UK

    • Rebecca E. Meadows
    • , Kevin W. Leslie
    • , Rhona Savin
    • , Fiona Bell
    •  & Rachel H. Munday
  4. Lab of Computational Chemistry and Drug Design, School of Chemical Biology and Biotechnology, Peking University, Shenzhen Graduate School, Shenzhen, China

    • Olaf Wiest

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Contributions

E.H. and A.R.R. wrote the code, J.W. and E.L. performed calculations, R.H.M., R.M., K.W.L., R.S. and F.B. performed experiments. All authors designed the study, analyzed the data and contributed to the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Rachel H. Munday or Olaf Wiest or Per-Ola Norrby.

Supplementary information

  1. Supplementary Information

    Supplementary Methods, Supplementary Figures 1–5, Supplementary Tables 1–4, Supplementary References

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DOI

https://doi.org/10.1038/s41929-018-0193-3

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