| Description |
Asymmetric catalysis is a powerful method for synthesizing enantiomerically enriched chiral building blocks. Detailed understanding of how catalysts impart facial bias on prochiral substrates has the potential to enable improved catalyst design and increase catalyst applicability. To this end, linear free energy relationships have been used to relate catalyst properties to enantioselectivity, enabling greater understanding of key catalyst-substrate interactions. Linear free energy relationships also can allow prediction of catalyst performance prior to their preparation. In this dissertation, several linear free energy relationships are described with a focus on developing predictive power and understanding the mechanism of asymmetric induction. In asymmetric catalysis, steric effects are often implicated as key components in imparting enantioselectivity; however, they are typically treated empirically. In Chapter 2, steric parameters, particularly Charton parameters, are used to quantify ligand steric effects in the Nozaki-Hiyama-Kishi allylation of aryl aldehydes and ketones. Multidimensional linear free energy relationships, which simultaneously quantified the steric effects at both positions, are determined and used to predict ligand performance. The multivariate linear free energy relationships have guided the design of a new ligand scaffold capable of enantioselective propargylation of ketones, which is discussed in Chapter 3. The multivariate relationships were expanded to include nonsteric terms, which enabled the development of an electronically and sterically optimized catalytic system for the enantioselective propargylation of ketones, yielding enantioenriched homopropargyl alcohols. The multivariate approach to describing substituent effects in asymmetric catalysis led to the evaluation of Sterimol parameters. Chapter 4 gives five examples of data sets where Sterimol values led to better correlation and predictive power than the previously used Charton parameters. The computational basis of the Sterimol parameters allows for greater interpretation of the models in which they are utilized. Quantifying the factors that lead to enantioselective outcomes is a key challenge in asymmetric catalysis. Combining steric parameters, multidimensional analysis, and the principles of experimental design can lead to increased predictive power in asymmetric catalysis. |
