COPCOP: A Novel Algorithm and Parallel Optimization Framework for Co-Evolutionary Domain Detection

Co-evolution exists ubiquitously in biological systems. At the molecular level, interacting proteins, such as ligands and their receptors and components in protein complexes, co-evolve to maintain their structural and functional interactions. Many proteins contain multiple functional domains interacting with different partners, making co-evolution of interacting domains occur more prominently. Multiple methods have been developed to predict interacting proteins or domains within proteins by detecting their co-variation. This strategy neglects the fact that interacting domains can be highly co-conserved due to their functional interactions. Here we report a novel algorithm COPCOP to detect signals of both co-positive selection (co-variation) and co-purifying selection (co-conservation). Results show that our algorithm performs well and outperforms the popular co-variation analysis program CAPS. We also design and implement a multi-level parallel acceleration strategy for COPCOP based on Tianhe-2 CPU-MIC heterogeneous supercomputer system to meet the need of large-scale co-evolutionary domain detection.