A peer-reviewed version of this preprint was published in PeerJ on 10 July 2017. View the peer-reviewed version (peerj.com/articles/cs-120), which is the preferred citable publication unless you specifically need to cite this preprint. Swainston N, Currin A, Green L, Breitling R, Day PJ, Kell DB. 2017. CodonGenie: optimised ambiguous codon design tools. PeerJ Computer Science 3:e120 https://doi.org/10.7717/peerj-cs.120 CodonGenie: optimised ambiguous codon design tools Neil Swainston Corresp., 1 , Andrew Currin 1 , Lucy Green 1 , Rainer Breitling 1, 2 , Philip J Day 3 , Douglas B Kell 1, 2 1 Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), University of Manchester, Manchester, United Kingdom 2 School of Chemistry, University of Manchester, Manchester, United Kingdom 3 Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom Corresponding Author: Neil Swainston Email address:
[email protected] CodonGenie, freely available from http://codon.synbiochem.co.uk , is a simple web application for designing ambiguous codons to support protein mutagenesis applications. Ambiguous codons are derived from specific heterogeneous nucleotide mixtures, which create sequence degeneracy when synthesised in a DNA library. In directed evolution studies, such codons are carefully selected to encode multiple amino acids. For example, the codon NTN, where the code N denotes a mixture of all four nucleotides, will encode a mixture of phenylalanine, leucine, isoleucine, methionine and valine. Given a user-defined target collection of amino acids matched to an intended host organism, CodonGenie designs and analyses all ambiguous codons that encode the required amino acids.