Computational Prediction of Enantioselectivity in Metal-Catalyzed Reactions

With the support of the Chemical Catalysis Program in the Division of Chemistry, Professors Olaf Wiest and Paul Helquist at the University of Notre Dame are developing computational methods for the fast and accurate prediction of the stereochemical, or three-dimensional, outcomes of chemical reactions. In many reactions, two different products known as enantiomers or mirror images can be formed. For applications such as pharmaceuticals, sometimes only one of the enantiomers is beneficial while the other may have no benefit or may even have deleterious effects. Traditional methods based entirely on experimental studies to find a means to selectively generate only one enantiomer are slow and expensive. They make use of largely trial-and-error approaches often requiring hundreds of experiments to be performed with expensive reagents and catalysts and, in the meantime, generate unnecessary chemical waste. In contrast, the computational methods that are the basis of the current project are a fast and cost-efficient means to predict specific catalysts that will produce the desired enantiomeric outcome. These predictions accelerate and support follow-up experimental studies. This work will likely have a significant broader impact because it is performed in close collaboration with AstraZeneca, a major international pharmaceutical company. They not only incorporate the Notre Dame methods into their process research to foster innovation, but also provide unique professional development opportunities for the students working on the project through industrial internships, interdisciplinary training at AstraZeneca in Sweden, and regular interactions with industrial researchers. The two lead investigators are strongly committed to broadening participation with a long track record of offering undergraduate research opportunities to students from underrepresented groups, as instructors in the Galvin Scholars Program for students from less well-prepared educational backgrounds, and by serving as mentors in the Building Bridges Program for underrepresented minority students. Professors Helquist and Wiest at the University of Notre Dame continue the development of a virtual screening tool for enantioselective catalysis (CatVS) that uses transition state force fields (TSFFs) derived using the quantum-guided molecular mechanics (Q2MM) method. This includes several new methods for the optimization of TSFFs that improve the accuracy of TSFF combinations with literature force fields, the semi-automation of the fitting procedure using a hybrid epsilon-constraint/PSO method; improved workflows for the generation and screening of virtual libraries (LibGen), new interfaces to other programs for conformational searching and TSFFs for new reactions selected by the team in collaboration with their industrial partners. Once tested and validated, all new developments will be incorporated in the Q2MM/LibGen/CatVS code that will continue to be available to the scientific community free of charge at github.com/q2mm. The impact of this method will be demonstrated in applications ranging from Ir-catalyzed hydroaminations of unactivated alkenes through novel nickel-catalyzed cross-coupling reactions to the computer-assisted design of new ligand classes for enantioselective synthesis. The combined computational and experimental approach, combined with the close collaboration with AstraZeneca, provides a unique interdisciplinary training environment for undergraduate and graduate students. 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.