Discovering Modular Catalysts for Asymmetric Synthesis with Computation

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Dr. Robert Paton of the Department of Chemistry at Colorado State University is supported by an award from the Chemical Catalysis program in the Division of Chemistry to develop new computational approaches for chiral catalyst discovery. The preparation of chiral molecules plays a vital and enabling role in the discovery of medicines, agrochemicals, and materials. Newly approved drugs are dominated by single enantiomer, chiral compounds. Dr. Paton’s group develops new methods of theory and simulation to accelerate the discovery of new catalysts and new reactions for the highly-selective construction of chiral molecules. This will go hand-in-hand with new mechanistic discoveries and collaborations with experimentalists that broaden the horizons of participating scientists. The research team, which will include undergraduate and postgraduate researchers, will learn a diverse array of skills well-aligned with the modern STEM workplace and will engage the public through outreach events in Colorado.There is a widely recognized need for rational approaches to replace empirical screening in the discovery of new catalyst structures. In this project, Dr. Robert Paton is developing computational protocols that combine small-molecule fragments adhering to the synthetic logic of known coupling reactions to construct and optimize catalyst architectures for asymmetric transformations. Virtual catalyst libraries are being assembled and mapped in an automated fashion using computational chemistry descriptions of steric and electronic properties. A triaged approach is being developed that directs in-depth quantum chemical efforts towards the most profitable areas of catalyst space to promote enantioselective hydrogen-bonding phase-transfer catalysis, bifunctional organocatalysis, and transformations involving metal-phosphoramidite complexes. In each case, new mechanistic discoveries are revealing the structural pre-requisites for catalytic activity and high enantioselectivity for a given substrate. The automated construction of large catalyst libraries, and the computation of steric and electronic parameters are providing that large datasets of use to the broader community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.