Quantifying Structural Effects of Amino Acid Ligands in Pd(II)-Catalyzed Enantioselective C-H Functionalization Reactions

Delineating complex ligand effects on enantioselectivity is a longstanding challenge in asymmetric catalysis. With alpha-amino acid ligands, the essential difficulty lies in accurately describing integrated perturbations induced by simultaneous variation about the alpha side chain and N protecting group of the ligand, which hampers an intuitive understanding of the structure enantioselectivity relationships: To deconvolute such complexity in chiral amino acid enabled enantioselective C-H functionalization reactions, a computational organometallic model system was developed. Whereas a model based only on a conventional results in diminished predictive power, the ground state Pd(II)-based models display an excellent ability to, describe the observed enantioselectivity. These structures were leveraged using a multivariate modeling approach to successfully describe Pd(II)-catalyzed C-H alkylation, alkenylation, and two C-H arylation reactions, wherein descriptors of torsion angle, percent buried volume, and NBO charge showed quantitative relevance to predict: enantiomeric excess. On the basis of the insights revealed in these case studies, an optimal set of amino acid ligands, is suggested to provide maximum information in a screening campaign.