Exploring the diversity of complex metabolic networks

Bioinformatics. 2005 Apr 15;21(8):1603-9. doi: 10.1093/bioinformatics/bti213. Epub 2004 Dec 21.

Abstract

Motivation: Metabolism, the network of chemical reactions that make life possible, is one of the most complex processes in nature. We describe here the development of a computational approach for the identification of every possible biochemical reaction from a given set of enzyme reaction rules that allows the de novo synthesis of metabolic pathways composed of these reactions, and the evaluation of these novel pathways with respect to their thermodynamic properties.

Results: We applied this framework to the analysis of the aromatic amino acid pathways and discovered almost 75,000 novel biochemical routes from chorismate to phenylalanine, more than 350,000 from chorismate to tyrosine, but only 13 from chorismate to tryptophan. Thermodynamic analysis of these pathways suggests that the native pathways are thermodynamically more favorable than the alternative possible pathways. The pathways generated involve compounds that exist in biological databases, as well as compounds that exist in chemical databases and novel compounds, suggesting novel biochemical routes for these compounds and the existence of biochemical compounds that remain to be discovered or synthesized through enzyme and pathway engineering.

Availability: Framework will be available via web interface at http://systemsbiology.northwestern.edu/BNICE (site under construction).

Contact: vassily@northwestern.edu or broadbelt@northwestern.edu

Supplementary information: http://systemsbiology.northwestern.edu/BNICE/publications.

Publication types

  • Evaluation Study
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Amino Acids, Aromatic / metabolism*
  • Animals
  • Biodiversity
  • Computer Graphics
  • Computer Simulation
  • Energy Metabolism / physiology*
  • Feasibility Studies
  • Humans
  • Models, Biological*
  • Models, Chemical*
  • Multienzyme Complexes / metabolism*
  • Signal Transduction / physiology*
  • User-Computer Interface*

Substances

  • Amino Acids, Aromatic
  • Multienzyme Complexes