We have expanded the ligand knowledge base for monodentate P-donor ligands (LKB-P, Chem. Eur. J. 2006, 12, 291-302) by 287 ligands and added descriptors derived from computational results on a gold complex [AuClL]. This expansion to 348 ligands captures known ligand space for this class of monodentate two-electron donor ligands well, and we have used principal component analysis (PCA) of the descriptors to derive an improved map of ligand space. Potential applications of this map, including the visualization of ligand similarities/differences and trends in experimental data, as well as the design of ligand test sets for high-throughput screening and the identification of ligands for reaction optimization, are discussed. Descriptors of ligand properties can also be used in regression models for the interpretation and prediction of available response data, and here we explore such models for both experimental and calculated data, highlighting the advantages of large training sets that sample ligand space well. † Development of a Ligand Knowledge Base, Part 6. See refs 1-5 for Parts 1-5.

The ligand knowledge base approach has been extended to capture the properties of 108 bidentate P,P- and P,N-donor ligands. This contribution describes the design of the ligand set and a range of DFT-calculated descriptors, capturing ligand properties in a variety of chemical environments. New challenges arising from ligand conformational flexibility and donor asymmetry are discussed, and descriptors are related to other parameters, such as the ligand bite angle. A novel map of bidentate ligand space, potentially useful in catalyst design and discovery, has been derived from principal component analysis of the resulting LKB-PP descriptors. In addition, a range of multiple linear regression models have been derived for both experimental and calculated data, considering ligand bite angles in square-planar palladium complexes and ligand dissociation energies from octahedral chromium complexes, respectively. These data sets were fitted with models based on LKB descriptors to explore the transferability of descriptors to different coordination environments and to illustrate potential applications of such models in catalyst design, allowing predictions about novel or untested ligands.

The kinetics of Pd-catalyzed Tsuji-Trost allylation employing simple phosphine ligands (L = Ar3P, etc.) are consistent with turnover-limiting nucleophilic attack of an electrophilic [L2Pd(allyl)]+ catalytic intermediate. Counter-intuitively, when L is made more electron donating, which renders [L2Pd(allyl)]+ less electrophilic (by up to an order of magnitude), higher rates of turnover are observed. In the presence of catalytic NaBAr'F, large rate differentials arise by attenuation of ion-pair return (via generation of [L2Pd(allyl)]+ [BAr'F]-) a process that also increases the asymmetric induction from 28 to 78% ee in an archetypal asymmetric allylation employing BINAP (L*) as ligand. There is substantial potential for analogous application of [M]n+([BAr'F]-)n cocatalysis in other transition metal catalyzed processes involving an ionic reactant or reagent and an ionogenic catalytic cycle.

We have expanded the ligand knowledge base for bidentate P,P- and P,N-donor ligands (LKB-PP, Organometallics20082713721383) by 208 ligands and introduced an additional steric descriptor (nHe8). This expanded knowledge base now captures information on 334 bidentate ligands and has been processed with principal component analysis (PCA) of the descriptors to produce a detailed map of bidentate ligand space, which better captures ligand variation and has been used for the analysis of ligand properties.