The ability to manipulate the concentration of individual proteins in a cell is limited, for example, by the lack of knowledge of the factors that regulate protein stability. In this project the response of yeast cells to oxidative stress will be used to develop predictive models of protein degradation based on protein sequence and structure. The approach will employ mass spectrometry and bioinformatics to combine proteomic data (including protein ubiquitination status and degradation) with information on protein sequence and structure to learn features that impact protein stability. Predictions will be validated in targeted experiments. Broader Impacts: Interdisciplinary training will be provided to graduate students and postdoctoral fellows, and engagement with high-school students will be achieved through participation in the American Museum of Natural History's LANG program.
