Catalysis of Organic..

Rothenberg et al. 267Table 1. Partial representation of the initial Heck reaction dataset.Cat t ºC ArX a Alkene a Solv. a Yield% TON TOF h –1 Ref.1 50 PhI NBA DMA 100 41 1000 (18)2 30 CNBr NBA DMA 50 1 50 (18)3 100 PhI TBA Et 3 N 98 57 981 (17)4 100 NO 2 Br TBA Et 3 N 100 14 100 (17)5 85 PhI EtA DMF 100 222 1000 (15)6 85 PhI EtA DMF 48 209 480 (15)7 85 PhI EtA DMF 63 191 630 (15)8 120 PhBr NBA DMA 91 113 910 (22)9 120 NO 2 Br NBA DMA 95 237 950 (22)10 60 PhOTf DHF THF 85 4.25 1 (23)11 120 MeOBr styrene TBAB 99 2.78 50 (24)a NBA = n-butyl acrylate; TBA = tert-butyl acrylate; EtA = ethyl acrylate; CNBr =p-CN(C 6 H 4 )Br; NO 2 Br = p- NO 2 (C 6 H 4 )Br; MeOBr = p- CH 3 O(C 6 H 4 )Br; TBAB =tetrabutylammonium bromide.Already at this early stage, using simple 2D descriptors, the model yieldsimportant mechanistic information: The correlation for the TON and the TOFdepends strongly on the reaction temperature, with a cut-off point at 120 ºC (Table2). The chemical reason for this is that Pd nanoclusters form much faster above 120ºC (25), and the reaction follows a pathway that is independent of the ligand.Table 2. PLS model prediction quality as a function of reaction temperatureFigure ofmerit aFull dataset(253 reactions)=120 ºC(191 react.)TON 0.23 0.79 0.57 0.27TOF 0.18 0.79 0.47 0.32Product yield 0.86 0.92 0.90 0.87We now select 10,000 bidentate catalysts at random (because this is the firstiteration) from the large space generated using building blocks 1–29, and calculatethe 2D descriptor values for these ligands. Projecting the results for these 10,000structures on the PLS model gives the predicted figures of merit (Figure 4). Fromthis ‘rough screening’ we choose the best 206 structures, by combining the 100 bestperformingstructures for each figure of merit (the TON and TOF show a highoverlap, which is to be expected).