Predicting Protein-Protein Interaction by the Mirrortree Method: Possibilities and Limitations |
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| Authors: | Hua Zhou Eric Jakobsson |
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| Affiliation: | 1. Department of Biochemistry, University of Illinois, Urbana-Champaign, Illinois, United States of America.; 2. Beckman Institute, National Center for Supercomputing Applications, Program in Biophysics and Computational Biology, Department of Molecular and Integrative Physiology, University of Illinois, Urbana-Champaign, Illinois, United States of America.; National Institutes of Health, United States of America, |
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| Abstract: | Molecular co-evolution analysis as a sequence-only based method has been used to predict protein-protein interactions. In co-evolution analysis, Pearson''s correlation within the mirrortree method is a well-known way of quantifying the correlation between protein pairs. Here we studied the mirrortree method on both known interacting protein pairs and sets of presumed non-interacting protein pairs, to evaluate the utility of this correlation analysis method for predicting protein-protein interactions within eukaryotes. We varied metrics for computing evolutionary distance and evolutionary span of the species analyzed. We found the differences between co-evolutionary correlation scores of the interacting and non-interacting proteins, normalized for evolutionary span, to be significantly predictive for proteins conserved over a wide range of eukaryotic clades (from mammals to fungi). On the other hand, for narrower ranges of evolutionary span, the predictive power was much weaker. |
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