Protein structure prediction by a data-level parallel algorithm

We have developed a software system, PHI-PSI, on the Connection Machine that uses a parallel algorithm to retrieve and use information from a database of 112 known protein structures (selected from the Brookhaven Protein Databank) to predict the structures of other proteins. The φ and angles of each amino acid (the angles each amino acid forms with its immediate neighbors) in a protein are used to represent its 3-D structure. PHI-PSI's algorithm is based on the idea of Memory-based reasoning (MBR) [10] and extends it to include a recursive procedure to refine its initial prediction and a “window” of varying sizes to look at different contexts of an input. PHI-PSI has been tested with all the available data. Initial results show that it performs better than distribution-based guesses for most of the φ and angle values.