Running Title: Protein Structure Prediction With Visual CBR

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 similar 3D protein structure. The success of this method provides support for the notion that changing representations can enable similarity metrics in case-based reasoning