With this award, the Chemical Catalysis Program of the NSF Division of Chemistry is supporting the research of Professor Daniel Weix at the University of Wisconsin-Madison and Dr. Eric Hansen at Pfizer to explore new methods to find better catalysts for chemical reactions. Metal-catalyzed reactions are the key to improving the stewardship of the U.S.'s vast petrochemical resources and to discovering innovative, new medicines. Existing technology is based around scarce metals, such as palladium and rhodium, but recent developments with more earth-abundant metals, such as nickel, copper, and iron, show great promise. Unfortunately, there are currently few catalysts based around these more environmentally friendly and less expensive metals. This industrial-academic partnership is discovering new catalysts by mining an untapped resource, pharmaceutical compound libraries. Using these libraries of knowledge, the team is mining data to find new catalysts and to gather information on what properties make a good catalyst. Analysis of the collected data by researchers at Pfizer and UW-Madison, with the assistance of Professor Matthew Sigman at the University of Utah, guides the prediction of new catalysts and catalyst selection. The newly discovered catalysts are being made available to researchers through a partnership with Millipore-Sigma. This combination of experimental and computational training is preparing students to advance the use of data science in chemistry, an area that is rapidly growing in importance. This training includes students who are currently underrepresented in chemistry through partnerships with existing and new UW-Madison programs: the Chemistry Opportunities Program, Partners for Graduate School Experience in Chemistry, and the American Chemical Society BRIDGE to the Doctorate program.
The UW-Madison team, led by Professor Weix, and the Pfizer team, led by Dr. Hansen, are systematically searching the very large Pfizer compound library for new ligands using an iterative experimental and computational approach inspired by fragment-based drug discovery. The goals of this collaboration are to discover new privileged ligands and to develop broadly applicable parameters and models. Diverse potential ligands sourced from the compound library are being screened against known reactions with different metal and ligand requirements to find new ligand core structures. These core structures are then being optimized using conventional methods. The data gathered is analyzed, in collaboration with Professor Sigman, to provide an understanding of which properties (if any) are universal for useful ligands and to predict improved ligands. The impacts of this this research program extend to the development of new ligands and versatile ligand precursors that are immediately made commercially available from Millipore-Sigma. The research may also result in better parameters and models that are useful for constructing a more diverse array of ligand types. The large data sets are helpful for developing new computational approaches made available through data repositories.
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.
