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Despite significant progress in diagnosis and treatment, cancer remains Canada’s leading cause of death. Although scientists have made major efforts in identifying mutations in some cancers, it is still not known how these mutations cause cancer.

Cancer is often related to the disruption of regulatory mechanisms in the cell, including auto-inhibition, a process that allows proteins to switch their functions on and off. Mutations can alter these protein switches, which can lead to changes in cell behaviour and ultimately cancer. However, there is no easy way to determine when cancer-causing mutations affect auto-inhibitory switches.

Dr. Joerg Gsponer and his team developed the first computational tools that allow identifying autoinhibitory switches in proteins based on available genomic and proteomic information and have made their server and source code freely accessible to the scientific community: Cis-regPred is the world’s first predictor to identify cis autoinhibitory switches in proteins; MoRFchibiSYSTEM is the most accurate predictor to identify molecular recognition features (MoRGs) to date.

With these tools, cancer driving mutations that disrupt CRE function can be isolated, potentially identifying novel drug targets for precision medicine.