Uncovering Subtle Ligand Effects of Phosphines Using Gold(I) Catalysis

Abstract

Herein, we report the integration of simple linear regressions with gold(I) catalysis to interrogate the influence of phosphine structure on metal-catalyzed organic transformations. We demonstrate that observed product ratios in [4 + 3]/[4 + 2] cycloisomerization processes are influenced by both steric and electronic properties of the phosphine, which can be represented by the Au-Cl distance. In contrast, the observed selectivity of a similar [2 + 3]/[2 + 2] cycloisomerization is governed by L/B1, a steric parameter. Using this correlation, we were able to accurately predict the selectivity of a previously untested, Buchwald-type ligand to enhance selectivity for the same transformation. This ligand found further utility in increasing the selectivity of a previously reported gold-catalyzed cycloisomerization/arylation of 1,6-enynes by ~1 kcal/mol.

Computational Ligand Descriptors for Catalyst Design

“…IR stretching frequencies L2EP in isostructural Rh complexes 197 Pyridine-oxazoline ligands (36), analysis of Pd-catalysed redox-relay Heck reaction and Ru-catalysed Carroll rearrangement Ligand descriptors (IR vibrational modes, NBO charges, Sterimol parameters), metal complex-derived descriptors (PdCl2(LL), metal NBO charges, M-L bonding orbital energies, Sterimol parameters, %Vbur, structural parameters including bite angles, M-D distances etc.). 198 -Amino acid ligands (37), used in Pdcatalysed C-H functionalisation reactions Molecular descriptors harvested from calculations on ligand and Pdcoordinated ligand, including NBO charges, %Vbur, structural parameters.…”

“…MLR using the chosen descriptors is followed by model evaluation through cross-validation and external testing, with a view to determining whether the model can be used for prediction. This workflow has been applied to a wide range of reactions, 13,14,36,37,90,123,154,198,199,201,202 and we have noted the use of different ligand descriptors in such studies throughout section 2.…”

“…While this approach depends on the availability of relatively extensive experimental data, other studies from this group have shown how the chemical insights gained from smaller-scale analyses of ligand effects can guide synthetic work towards promising targets, 37,123 neatly bridging LFER/physical organic chemistry approaches with large-scale descriptor calculations.…”

Parameterization of Acyclic Diaminocarbene Ligands Applied to a Gold(I)-Catalyzed Enantioselective Tandem Rearrangement/Cyclization

“…2 Notwithstanding the pace of these developments, asymmetric catalysis with gold complexes has largely relied on chiral phosphorus based ancillary ligands. 3 Though carbene ligands have been demonstrated to induce differential reactivity in gold catalysis, 4 their utility as chiral ligands has been limited by the lack of modularity and insights into how specific alterations can be leveraged to deliver effective and selective catalysts. 5 These limitations are not unique to gold catalysis, as highly enantioselective transition metal-catalyzed reactions using chiral carbene ligands remain relatively rare compared to their phosphorus-based counterparts.…”

Quantitative Modeling of Bis(pyridine)silver(I) Permanganate Oxidation of Hydantoin Derivatives: Guidelines for Predicting the Site of Oxidation in Complex Substrates

“…One of our laboratories has developed an effective methodology for parameterization of complex chemical transformations to glean key insights that inform further development and application of the chemistry, as demonstrated in several case studies including fluorination, gold catalyzed cyclization, and rhodium-catalyzed C–H functionalization. 11 Herein, we describe the development of an informative model using a library of simple hydantoins as a training substrate-set by relating the relative rates of oxidation to various calculated molecular descriptors. The resulting model highlights the impact of the Hammett parameter and percent buried volume on the oxidation outcome, and when applied to analysis of new case studies, the model can reliably predict and explain the experimentally observed oxidation of complex diketopiperazine substrates.…”