Unlike traditional drugs that bind and block the activity of key proteins in cancer cells, a new generation of drugs can eliminate proteins by hijacking the protein degradation machinery within cells. Dr. Tokheim is developing computational models that can identify degradable proteins that are linked to the development of human cancers. By leveraging big data from thousands of tumor profiles and a novel statistical and deep learning model, he will conduct an unbiased search for candidate proteins that can be verified experimentally. This research may lead to the development of drugs targeting protein degradation as a potent and selective way to treat a variety of human cancers.
Dr. Tokheim has developed computational methods aimed to predict dysregulated protein degradation by the Ubiquitin-Proteasome System (UPS) in cancer. First, this involved developing two machine learning approaches (deepDegron and a Random Forest algorithm) to predict degron sequences in proteins. He leveraged a permutation test to evaluate whether mutations in cancer significantly disrupted degrons. Second, he developed a regression model to associate mutated UPS genes with transcription factors based on multi-omic data integration.
