Identifying Evolutionarily Conserved Protein Interaction Modules Using GraphHopper

We study the question of detecting Conserved Protein Interaction Modules (CPIMs) in two protein-protein interaction (PPI) networks. A CPIM contains a pair of groups of interacting proteins, one in each PPI network, that share a high degree of evolutionary conservation. We propose a novel algorithm called GraphHopper that analyzes two PPI networks to find CPIMs. GraphHopper keeps the two PPI networks separate and connects them using potentially orthologous pairs of proteins. GraphHopper finds CPIMs by “hopping” from one network to another using orthology relationships. By decoupling the degree of evolutionary conservation in a CPIM from the quality of the PPIs in a CPIM, GraphHopper succeeds in finding CPIMs with a wide variety of topologies that cannot be detected by previous algorithms. Our comparisons demonstrate that GraphHopper is competitive with NetworkBlast and Match-and-Split, two state-of-the-art algorithms for computing CPIMs. Upon applying GraphHopper to human, fly, and yeast PPI networks, we find a number of CPIMs involved in fundamental processes of the cell that are conserved in all three species. We present the first global map of human-fly CPIMs. This map sheds light on the conservation of protein interaction modules in multi-cellular organisms. Many CPIMs Corresponding author. related to development and the nervous system emerge only in the human-fly comparison. For example, a set of 10 interconnected CPIMs suggest that fly proteins involved in eye development may have human orthologs that have evolved functions related to blood clotting, vascular development, and structural support.