A combinatorial approach to the identification of self-assembled ligands for rhodium-catalysed asymmetric...

An effective and efficient means to catalyst discovery is the high-throughput screening of catalyst libraries. However, the current status of this approach suffers from a number of limitations, namely access to structurally diverse and meaningful ligand libraries and the enormous effort required for massive parallel screening of the resulting catalysts. We report an integrated solution to these drawbacks, which combines a diversity-oriented ligand synthesis, a catalyst-generation process driven by self-assembly and, finally, a combinatorial iterative library deconvolution strategy to identify the optimal catalyst. As a test case, rhodium-catalysed asymmetric hydrogenation was studied and, from a library of 120 self-assembling catalysts, highly enantioselective catalysts for the asymmetric hydrogenation of different olefinic substrates were identified within 17 experiments. Comparison of the results of the iterative library deconvolution strategy with those of the classic parallel-screening process confirmed the validity of this approach.