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Computational prediction of small-molecule catalysts

Nature volume 455, pages 309–313 (2008)Cite this article

Abstract

Most organic and organometallic catalysts have been discovered through serendipity or trial and error, rather than by rational design. Computational methods, however, are rapidly becoming a versatile tool for understanding and predicting the roles of such catalysts in asymmetric reactions. Such methods should now be regarded as a first line of attack in the design of catalysts.

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Figure 1: Time required to compute molecular structures.
Figure 2: Successful computational predictions of non-catalytic reactions.
Figure 3: Transition structures of the Hajos–Parrish reaction.
Figure 4: Successful computational predictions of catalysts.

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Acknowledgements

We are grateful to the University of California, Los Angeles, as well as to the National Institute of General Medical Sciences (grant GM 36700) and the National Science Foundation (grant CHE-0548209), for financial support. We also thank C. Legault for the use of CYLview, and M. Tarini, P. Cignoni and C. Montani for assistance in using QuteMol.

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Authors and Affiliations

  1. Department of Chemistry and Biochemistry, K. N. Houk and Paul Ha-Yeon Cheong are at the University of California, Los Angeles, 607 Charles E. Young Drive East, Los Angeles, California 90095, USA.,

    K. N. Houk & Paul Ha-Yeon Cheong

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Correspondence should be addressed to K.N.H. (houk@chem.ucla.edu).

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Houk, K., Cheong, PY. Computational prediction of small-molecule catalysts. Nature 455, 309–313 (2008). https://doi.org/10.1038/nature07368

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