Computational Methods Enable the Prediction of Improved Catalysts for Nickel-Catalyzed Cross-Electrophile Coupling

Cross-electrophile
coupling has emerged as an attractive and efficient
method for the synthesis of C­(sp2)–C­(sp3) bonds. These reactions are most often catalyzed by nickel complexes
of nitrogenous ligands, especially 2,2′-bipyridines. Precise
prediction, selection, and design of optimal ligands remains challenging,
despite significant increases in reaction scope and mechanistic understanding.
Molecular parameterization and statistical modeling provide a path
to the development of improved bipyridine ligands that will enhance
the selectivity of existing reactions and broaden the scope of electrophiles
that can be coupled. Herein, we describe the generation of a computational
ligand library, correlation of observed reaction outcomes with features
of the ligands, and the in silico design of improved bipyridine ligands
for Ni-catalyzed cross-electrophile coupling. The new nitrogen-substituted
ligands display a 5-fold increase in selectivity for product formation
versus homodimerization when compared to the current state of the
art. This increase in selectivity and yield was general for several
cross-electrophile couplings, including the challenging coupling of
an aryl chloride with an N-alkylpyridinium salt.