Virtual Ligand-Assisted Optimization: A Rational Strategy for Ligand Engineering

Ligand engineering is one of the most important, but labor-intensive processes in the development of transition metal catalysis. Historically, this process has been streamlined by the invention of ligand descriptors such as Tolman’s electronic parameter and the cone angle. Analyzing reaction outcomes in terms of these parameters has enabled chemists to find important factors for designing optimal ligands. However, typical strategies for these analyses largely rely on regression approaches, which often requires many experimental data to understand non-intuitive trends. Here, we introduce the virtual ligand-assisted optimization (VLAO) method, a novel computational approach for ligand engineering. In this method, important features of ligands are identified by simple mathematical operations on equilibrium structures and/or transition states of interest, and derivative values of arbitrary objective functions with respect to ligand parameters are obtained. These derivative values are then used as a guiding principle to optimize ligands within the parameter space. The VLAO method was demonstrated in the optimization of monodentate and bidentate phosphine ligands including asymmetric quinoxaline-based ligands. In addition, we successfully found a highly selective ligand for the α-selective hydrogermylation of a terminal ynamide according to the suggested design principle by the VLAO method. These results would imply the potential utility of the VLAO method in optimizing wide variety of ligands in transition metal catalysis.