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Systems Metabolic Engineering pp 409–428Cite as

Targeted Metabolic Engineering Guided by Computational Analysis of Single-Nucleotide Polymorphisms (SNPs)

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 985))

Abstract

The non-synonymous SNPs, the so-called non-silent SNPs, which are single-nucleotide variations in the coding regions that give “birth” to amino acid mutations, are often involved in the modulation of protein function. Understanding the effect of individual amino acid mutations on a protein/enzyme function or stability is useful for altering its properties for a wide variety of engineering studies. Since measuring the effects of amino acid mutations experimentally is a laborious process, a variety of computational methods have been discussed here that aid to extract direct genotype to phenotype information.

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Acknowledgements

The authors would like to thank the Danish Research Council for Production and Technology Sciences and the Swedish Research Council (Vetenskapsrådet Grant no: 2008-2955) for financial support.

Author information

Authors and Affiliations

  1. Department of Chemical and Biological Engineering, Industrial Biotechnology, Chalmers University of Technology, Gothenburg, Sweden

    D. B. R. K. Gupta Udatha

  2. Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Kgs Lyngby, Denmark

    Simon Rasmussen & Thomas Sicheritz-Pontén

  3. School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, Hong Kong

    Gianni Panagiotou

  4. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark

    Gianni Panagiotou

Authors
  1. D. B. R. K. Gupta Udatha
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  2. Simon Rasmussen
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  3. Thomas Sicheritz-Pontén
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  4. Gianni Panagiotou
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Corresponding author

Correspondence to Gianni Panagiotou .

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Editors and Affiliations

  1. Cockrell School of Engineering, Dept. of Chemical Engineering, The University of Texas at Austin, E. Dean Keeton Street 200, Austin, 78712, Texas, USA

    Hal S. Alper

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Udatha, D.B.R.K.G., Rasmussen, S., Sicheritz-Pontén, T., Panagiotou, G. (2013). Targeted Metabolic Engineering Guided by Computational Analysis of Single-Nucleotide Polymorphisms (SNPs). In: Alper, H. (eds) Systems Metabolic Engineering. Methods in Molecular Biology, vol 985. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-299-5_20

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  • DOI: https://doi.org/10.1007/978-1-62703-299-5_20

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-298-8

  • Online ISBN: 978-1-62703-299-5

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