DESHARKY: automatic design of metabolic pathways for optimal cell growth.
BACKGROUND
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.


BACKGROUND
Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html
Rodrigo
Guillermo
G
Instituto de Biologia Molecular y Celular de Plantas, CSIC, Spain.
Carrera
Javier
J
Prather
Kristala Jones
KJ
Jaramillo
Alfonso
A
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D004926:Escherichia coli / Q000254:growth & development* / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D010802:Phylogeny; D020539:Sequence Analysis, Protein; D012984:Software