Journal Article

DESHARKY: automatic design of metabolic pathways for optimal cell growth

Guillermo Rodrigo, Javier Carrera, Kristala Jones Prather and Alfonso Jaramillo

in Bioinformatics

Volume 24, issue 21, pages 2554-2556
Published in print November 2008 | ISSN: 1367-4803
Published online September 2008 | e-ISSN: 1460-2059 | DOI:
DESHARKY: automatic design of metabolic pathways for optimal cell growth

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Motivation: The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context.

Results: We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size.

Availability: Software, a tutorial and examples are freely available and open source at


Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  2082 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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