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

• DOI: 10.1007/978-1-62703-299-5_20
• Publication Date: 2013-02-13T16:12:17Z
• Authors: D. B. R. K. Gupta...; Simon Rasmussen; Thomas Sicheritz-...; Gianni Panagiotou
• Keywords: Genome; Saccharomyces cerevisiae Proteins; Microbial genetic engineering; Genotyping Techniques; Protein Stability; Computational Biology; Saccharomyces cerevisiae; Sequence Analysis, DNA; Microbial genetic engineering.; Human genetics -- Variation.; Models, Biological; Polymorphism, Single Nucleotide; Human genetics -- Variation; Amino Acid Substitution; Metabolic Engineering; Chromosome polymorphism; Genetic markers.; Genetic markers; Chromosome polymorphism.; Sequence Alignment

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.