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A computational analysis of protein interactions in metabolic networks reveals novel enzyme pairs potentially involved in metabolic channeling

Journal of Theoretical Biology
Publication Date
DOI: 10.1016/j.jtbi.2007.09.042
  • Enzyme Interaction
  • Mapping
  • Yeast
  • E. Coli
  • Biology
  • Chemistry
  • Computer Science
  • Mathematics
  • Medicine


Abstract Protein–protein interactions are operative at almost every level of cell structure and function as, for example, formation of sub-cellular organelles, packaging of chromatin, muscle contraction, signal transduction, and regulation of gene expression. Public databases of reported protein–protein interactions comprise hundreds of thousands interactions, and this number is steadily growing. Elucidating the implications of protein–protein interactions for the regulation of the underlying cellular or extra-cellular reaction network remains a great challenge for computational biochemistry. In this work, we have undertaken a systematic and comprehensive computational analysis of reported enzyme–enzyme interactions in the metabolic networks of the model organisms Escherichia coli and Saccharomyces cerevisiae. We grouped all enzyme pairs according to the topological distance that the catalyzed reactions have in the metabolic network and performed a statistical analysis of reported enzyme–enzyme interactions within these groups. We found a higher frequency of reported enzyme–enzyme interactions within the group of enzymes catalyzing reactions that are adjacent in the network, i.e. sharing at least one metabolite. As some of these interacting enzymes have already been implicated in metabolic channeling our analysis may provide a useful screening for candidates of this phenomenon. To check for a possible regulatory role of interactions between enzymes catalyzing non-neighboring reactions, we determined potentially regulatory enzymes using connectivity in the network and absolute change of Gibbs free energy. Indeed a higher portion of reported interactions pertain to such potentially regulatory enzymes.

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