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Computational Elucidation of Selectivities and Mechanisms Performed by Organometallic and Bioinorganic Catalysts

  • Author(s): Grandner, Jessica Marie
  • Advisor(s): Houk, Kendall N
  • et al.
Abstract

Computational methods were used to determine the mechanisms and selectivities of organometallic-catalyzed reactions. The first half of the dissertation focuses on the study of metathesis catalysts in collaboration with the Grubbs group at CalTech. Chapter 1 describes the studies of the decomposition modes of several ruthenium-based metathesis catalysts. These studies were performed to better understand the decomposition of such catalysts in order to prevent decomposition (Chapter 1.2) or utilize decomposed catalysts for alternative reactions (Chapter 1.1). Chapter 2.1 describes the computational investigation of the origins of stereoretentive metathesis with ruthenium-based metathesis catalysts. These findings were then used to computationally design E-selective metathesis catalysts (Chapter 2.2). While the first half of the dissertation was centered around ruthenium catalysts, the second half of the dissertation pertains to iron-catalyzed reaction, in particular, iron-catalyzed reactions by P450 enzymes. The elements of Chapter 3 concentrate on the stereo- and chemo-selectivity of P450-catalyzed C-H hydroxylations. By combining multiple computational methods, the inherent activity of the iron-oxo catalyst and the influence of the active site on such reactions were illuminated. These discoveries allow for the engineering of new substrates and mutant enzymes for tailored C-H hydroxylation. While the mechanism of C-H hydroxylations catalyzed by P450 enzymes has been well studied, there are several P450-catalyzed transformations for which the mechanism is unknown. The components of Chapter 4 describe the use of computations to determine the mechanisms of complex, multi-step reactions catalyzed by P450s. The determination of these mechanisms elucidates how these enzymes react with various functional groups and substrate architectures and allows for a better understanding of how drug-like compounds may be broken down by human P450s.

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