Parallel Computational Biochemistry

Protein-protein interaction prediction and applications

Interactions among proteins are essential to many biological functions in living cells but experimentally detected interactions represent only a small fraction of the real interaction network. Computational protein interaction prediction methods have become important to augment the experimental methods (e.g. two-hybrid and TAP-tagging). Our parallel Protein Interaction Prediction Engine (PIPE) has been able to perform the first ever scan of the entire human proteome (3 months of 24/7 computation on a 1,000 processor cluster). Several previously unknown protein interactions that our method predicted have later been experimentally verified. An independent comparison study published in BMC Bioinformatics determined that PIPE outperforms other protein interaction prediction methods by a wide margin.

Current research projects include:

  • A collaboration with the Ottawa Hospital on new stem cell therapies for Muscular Dystrophy.
  • A collaboration with Agriculture Canada on soy bean resistance to Canadian winter temperatures.
  • A collaboration with WITS University in South Africa on the role of protein interactions in the evolutionary development of multi-cellular organisms. Check out the Video of F.Dehne's presentation at a Biochemistry/Evolution conference in Santa Barbara, Calif.


We have also launched a new spin-off company, Designed Biologics, which contributes towards the design of new targeted drugs based on protein interactions (e.g. immunotherapy for cancer treatment).


protein




    Lab (VSIM Building)