Visio-Spatial Case-Based Reasoning: A Case Study in Prediction of Protein Structure

We show that visio-spatial representations and reasoning can be used as a similarity metric for case-based protein structure prediction. Our system retrieves pairs of α-helices based on contact map similarity, then transfers and adapts the structure information to an unknown helix pair. We show that similar protein contact maps predict a similar three-dimensional protein structure. The success of this method provides support for the notion that changing representations can enable similarity metrics in case-based reasoning.