摘要

The development of asymmetric catalysts is typically driven by the experimental screening of potential catalyst designs. Herein, we demonstrate the design of asymmetric propargylation catalysts through computational screening. This was done using our computational toolkit AARON (automated alkylation reaction optimizer for N-oxides), which automates the prediction of enantioselectivities for bidentate Lewis base catalyzed alkylation reactions. A systematic screening of 59 potential catalysts built on 6 bipyridine N,N'-dioxide-derived scaffolds results in predicted ee values for the propargylation of benzaldehyde ranging from 45% (S) to 99% (R), with 12 ee values exceeding 95%. These data provide a broad set of experimentally testable predictions. Moreover, the associated data revealed key details regarding the role of stabilizing electrostatic interactions in asymmetric propargylations, which were harnessed in the design of a propargylation catalyst for which the predicted ee exceeds 99%.

  • 出版日期2016-11