P2K: Pattern to knowledge AI software for predicting residue interacting sites between proteins

Description of the invention

University of Waterloo (UW) researchers have developed a novel software P2K (Pattern to Knowledge) to discover deep knowledge inherent in bio-sequences such as DNA/RNA/Protein/Antibody. P2K uses novel autonomous and scalable algorithms to discover deep knowledge to reveal subtle functionality and relations and uses the knowledge discovered to enhance machine learning, achieving much better prediction results with explanation. The developed software receives two bio-sequences as the input and outputs the anticipated binding sites between the two.

Advantages

• Time/Cost reduction - uses sequence data only with no experiment setup or reliance on explicit prior knowledge.
• Higher accuracy – enhanced ML model by extracting predictive features from Protein to Protein-Interaction sequence data from the cloud.
• Robust to data noises - removes data noise and minimizes misinformation from entangled factors/sources.
• Flexible - applicable to other scenarios such as protein to antibody and protein to aptamer.
• Experimental comparison: a) 28% better prediction than existing solutions b) capable of revealing and confirming binding sites of interacting proteins not achievable by other methods.

Potential applications

• Assist in drug development
• Genomic, transcriptomic and proteomic data analysis
• Gene therapy – precision medicine
• Environmental detection (e.g., Aptamers, DNA barcodes)