title: Stoichiometric capacitance reveals the theoretical capabilities of metabolic networks.
abstract: BACKGROUND
  Metabolic engineering aims at modulating the capabilities of metabolic networks by changing the activity of biochemical reactions. The existing constraint-based approaches for metabolic engineering have proven useful, but are limited only to reactions catalogued in various pathway databases.
  
  
  RESULTS
  We consider the alternative of designing synthetic strategies which can be used not only to characterize the maximum theoretically possible product yield but also to engineer networks with optimal conversion capability by using a suitable biochemically feasible reaction called 'stoichiometric capacitance'. In addition, we provide a theoretical solution for decomposing a given stoichiometric capacitance over a set of known enzymatic reactions. We determine the stoichiometric capacitance for genome-scale metabolic networks of 10 organisms from different kingdoms of life and examine its implications for the alterations in flux variability patterns. Our empirical findings suggest that the theoretical capacity of metabolic networks comes at a cost of dramatic system's changes.
  
  
  BACKGROUND
  larhlimi@mpimp-golm.mpg.de, or nikoloski@mpimp-golm.mpg.de
  
  
  BACKGROUND
  Supplementary tables are available at Bioinformatics online.
authors.affiliation: Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany. larhlimi@mpimp-golm.mpg.de
authors.forename: Abdelhalim
authors.initials: A
authors.lastname: Larhlimi
authors.forename: Georg
authors.initials: G
authors.lastname: Basler
authors.forename: Sergio
authors.initials: S
authors.lastname: Grimbs
authors.forename: Joachim
authors.initials: J
authors.lastname: Selbig
authors.forename: Zoran
authors.initials: Z
authors.lastname: Nikoloski
mesh_terms: D001419:Bacteria / Q000378:metabolism; D002952:Citric Acid Cycle; D005943:Gluconeogenesis; D006019:Glycolysis; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological