Science Café | Data Science for Drug Discovery

• None event

Engineered proteins are synthetic novel proteins (not found in nature) that are designed to fulfill a predetermined biological function. Such proteins can be used as molecular markers, inhibitory agents, or drugs. We present a massively parallel computational tool for designing inhibitory proteins that are predicted to interact with a given target protein (and may inhibit the target’s cellular functions) while leaving non-target proteins unaffected (to minimize side-effects).

In collaboration with the Ottawa Hospital Research Institute, we have been designing protein-based drugs for muscular dystrophy treatments and are currently developing a protein-based drug to stop the interaction between the COVID spike protein and the human ACE2 protein.

About the Presenter

Dr. Frank Dehne received a MCS (Dipl. Inform.) from RWTH Aachen University, Germany and a PhD from the University of Wuerzburg, Germany. He is currently Chancellor’s Professor of Computer Science at Carleton University in Ottawa, and also Founding Director of Carleton’s Institute for Data Science.

Dr. Dehne’s research program is focused on improving the performance of big data analytics systems, in particular for business intelligence and computational biochemistry, through efficient parallel computing methods for multi-core processors, GPUs, processor clusters and clouds. He is serving or has served on the Editorial Boards of IEEE Transaction on Computers, Information Processing Letters, Journal of Bioinformatics Research and Applications, and Int. Journal of Data Warehousing and Mining.

He is a member and former vice-chair of the IEEE Technical Committee on Parallel Processing, and member of the ACM Symposium on Parallel Algorithms & Architectures Steering Committee. Since 2010, Dr. Dehne is a Fellow of the IBM Centre For Advanced Studies Canada (Business Intelligence and Business Analytics section).