Computational Investigations of the Diverse Factors Controlling the Mechanisms of Transition–Metal Catalyzed Carbon–Carbon Bond Forming Reactions

Transition metal-catalyzed reactions continue to be among the most popular synthetic methodologies for forming carbon-carbon bonds regio- and stereoselectively. Despite decades of advancements in the field, optimization of these reactions continues to be a challenge. In this work, density functional theory (DFT) calculations were performed on several transition metal-catalyzed carbon-carbon bond forming reactions including the Rh(I)-catalyzed asymmetric Pauson–Khand reaction (PKR) of 1,6-enynes, the Rh(I)-catalyzed allenic Pauson–Khand reaction (APKR), and Pd-catalyzed cross-coupling of chloroarenes. Analyses of key transition states on the reaction pathway were conducted to elucidate important insights into the dominant catalyst-substate interactions that govern transition state stability. The DFT study of the asymmetric Rh(I)-catalyzed PKR of 1,6-enynes revealed a dominant four-coordinate pathway, sterically determined mode of enantioselectivity, and factors impacting the effectiveness of the bidentate phosphine ligand class. Initial computational findings were then utilized to guide the expansion of the reaction scope and parameter selection for univariate regression. A set of molecular descriptors accurately predictive of the experimentally determined enantiomeric ratio were identified and validated by a follow-up DFT study. Careful examination of the ligand-substrate interactions during the enantioselectivity determining step of the APKR demonstrated that as the molecular complexity of the substrate increased, the level of stabilizing through-space interactions between the substrate and ligand increased in the major enantiomeric transition states. Structural information was gathered from the transition states of competing concerted and stepwise mechanisms of oxidative addition in the Pd-catalyzed cross-coupling of chloroarenes. The carbon-chlorine bond length in the chloroarene starting materials was identified as an important molecular descriptor that was then incorporated into a multivariate predictive model to determine the preference for a concerted or stepwise oxidative addition mechanism of a given substate.