Literature DB >> 23417803

Computational tools for guided discovery and engineering of metabolic pathways.

Matthew Moura1, Linda Broadbelt, Keith Tyo.   

Abstract

With a high demand for increasingly diverse chemicals, as well as sustainable synthesis for many existing chemicals, the chemical industry is increasingly looking to biosynthesis. The majority of biosynthesis examples of useful chemicals are either native metabolites made by an organism or the heterologous expression of known metabolic pathways into a more amenable host. For chemicals that no known biosynthetic route exists, engineers are increasingly relying on automated computational algorithms, as described here, to identify potential metabolic pathways. In this chapter, we review a broad range of approaches to predict novel metabolic pathways. Broadly, these can rely on biochemical databases to assemble known reactions into a new pathway or rely on generalized biochemical rules to predict unobserved enzymatic reactions that are likely feasible. Many programs are freely available and immediately useable by non-computationally experienced scientists.

Mesh:

Year:  2013        PMID: 23417803     DOI: 10.1007/978-1-62703-299-5_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  Computational evaluation of factors governing catalytic 2-keto acid decarboxylation.

Authors:  Di Wu; Dajun Yue; Fengqi You; Linda J Broadbelt
Journal:  J Mol Model       Date:  2014-06-10       Impact factor: 1.810

2.  Designing overall stoichiometric conversions and intervening metabolic reactions.

Authors:  Anupam Chowdhury; Costas D Maranas
Journal:  Sci Rep       Date:  2015-11-04       Impact factor: 4.379

  2 in total

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