N,N-Bidentate ligands are widely employed in Ni-catalyzed cross-electrophile coupling (CEC) reactions; however, it is often difficult to predict a priori which scaffold will provide optimal selectivity and yield for a reaction under development. More generally, for a given Ni-catalyzed reaction, models that provide structure-reactivity and structure-selectivity relationships across different N,N-bidentate ligand scaffolds remain elusive. Here, we report BUNNY, a density functional theory-based descriptor library of approximately 1100 N,N-bidentate ligands designed to support modeling tasks for Ni-catalyzed cross-coupling. Using BUNNY, a screening set of 31 ligands was selected to represent 7 ligand scaffolds, and the value of the screening set was demonstrated by modeling of two Ni-catalyzed CEC case studies. The first case study demonstrates that enantioselectivity can be modeled across different ligand families for two different benzylic electrophiles. The second case study used the screening library to collect ee data for an established Ni-CEC, which was used to guide development of an enantioselective Ni-catalyzed CEC of a different but related electrophile. Differences in descriptors selected by the enantioselectivity models for the two case studies inspired investigation of the radical capture and reductive elimination steps by DFT, which found that either step can be selectivity-determining, depending on the reaction. This work illustrates how BUNNY can be used to model reactivity and selectivity across ligand scaffolds, guiding reaction development and mechanistic understanding.
Gutiérrez-Valencia et al. (2026) studied this question.