Research
The Davis research group employs a combination of computational and physical organic chemistry to develop predictive models that address issues facing synthetic method development. The group is also employing these methods to develop molecular feature libraries for machine learning as part of an interdisciplinary collaboration working on antibiotic discovery.
We are working to elucidate the mechanisms and kinetic profiles of asymmetric functionalization reactions with a focus on determining the origin of enantioselection. In conjunction with our mechanistic studies, we are working to design and develop new catalysts that will predictably control regio- and stereochemistry in remote functionalizations.
We are working on the development of photo-aminocatalysts for application in stereoselective addition reactions and in the photophysical characterization of excited state intermediates in photoaminocatalytic reactions
We aim to develop novel small molecule inhibitors of several protein targets using a combination of computational modeling and chemical synthesis. The computational studies employed in this work provide us with a detailed understanding of the molecular mechanism of enzyme-catalyzed reactions. This information is then be used to “rationally design” compounds that will mimic the critical interactions between the substrate and enzyme.
We are working with academic and industrial collaborators to develop methods for improving data generation for machine learning in drug discovery. As part of an interdisciplinary research team, we are developing a machine learning approach aimed at expediting antibiotic discovery for Gram-negative bacteria by predicting and validating antibiotic activity.
Our trifecta of synthetic, kinetic and computational methods lends itself to addressing questions of reactivity and selectivity across a wide range of areas. We often collaborate with people to answer questions regarding the unusual behaviour of molecules and reactions or to capture a previously unobtainable compounds. So far, this work ranges from the study of polyaromatic hydrocarbons to transition metal complexes.
