Computational Biology CB_D0006

Title : Exploiting the Co-evolution of Interacting Proteins to Discover Interaction Specificity
Author : Arun K. Ramani1 and Edward M. Marcotte1,2*
Year : 2003
Place of publish :Science Direct
Abstract :

 Protein interactions are fundamental to the functioning of cells, and high
throughput experimental and computational strategies are sought to map
interactions. Predicting interaction specificity, such as matching members
of a ligand family to specific members of a receptor family, is largely an
unsolved problem. Here we show that by using evolutionary relationships
within such families, it is possible to predict their physical interaction
specificities. We introduce the computational method of matrix alignment
for finding the optimal alignment between protein family similarity
matrices. A second method, 3D embedding, allows visualization of interacting
partners via spatial representation of the protein families. These
methods essentially align phylogenetic trees of interacting protein families
to define specific interaction partners. Prediction accuracy depends
strongly on phylogenetic tree complexity, as measured with information
theoretic methods. These results, along with simulations of protein
evolution, suggest a model for the evolution of interacting protein families
in which interaction partners are duplicated in coupled processes. Using
these methods, it is possible to successfully find protein interaction
specificities, as demonstrated for .18 protein families.