Anat Milo - A data-intensive approach to mechanistic elucidation applied to chiral anion catalysis.

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      Publication Details (including relevant citation   information):

      Milo, Anat, Neel, Andrew J, Toste, F Dean, Sigman, Matthew S   2015 347 (6223) 737-743

      Abstract: Knowledge of chemical reaction   mechanisms can facilitate catalyst optimization, but extracting   that knowledge from a complex system is often challenging. Here,   we present a data-intensive method for deriving and then   predictively applying a mechanistic model of an enantioselective   organic reaction. As a validating case study, we selected an   intramolecular dehydrogenative C-N coupling reaction, catalyzed   by chiral phosphoric acid derivatives, in which   catalyst-substrate association involves weak, noncovalent   interactions. Little was previously understood regarding the   structural origin of enantioselectivity in this system. Catalyst   and substrate substituent effects were probed by means of   systematic physical organic trend analysis. Plausible   interactions between the substrate and catalyst that govern   enantioselectivity were identified and supported experimentally,   indicating that such an approach can afford an efficient means of   leveraging mechanistic insight so as to optimize catalyst design.

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