Identifying Evolutionarily Conserved Protein Interaction Modules Using GraphHopper

  • Authors:
  • Corban G. Rivera;T. M. Murali

  • Affiliations:
  • Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061;Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061

  • Venue:
  • BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
  • Year:
  • 2009

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Abstract

We study the question of detecting Conserved Protein Interaction Modules (CPIMs) in protein-protein interaction (PPI) networks. We propose a novel algorithm called GraphHopper that analyzes two PPI networks to find CPIMs. 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 reliability of the PPIs in a CPIM, GraphHopper finds CPIMs with a wide variety of topologies that previous algorithms cannot detect. GraphHopper is competitive with NetworkBlast and Match-and-Split, two state-of-the-art algorithms for computing CPIMs, on the task of recapitulating MIPS processes and complexes. 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. CPIMs 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.