CodonGenie: optimised ambiguous codon design tools
- Published
- Accepted
- Subject Areas
- Bioengineering, Bioinformatics, Biotechnology, Computational Biology, Synthetic Biology
- Keywords
- directed evolution, codon, protein engineering, industrial biotechnology, mutagenesis, enzyme engineering
- Copyright
- © 2017 Swainston et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. CodonGenie: optimised ambiguous codon design tools. PeerJ Preprints 5:e2797v1 https://doi.org/10.7287/peerj.preprints.2797v1
Abstract
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. The codons are ranked according to their efficiency in encoding the required amino acids while minimising the inclusion of additional amino acids and stop codons. Organism-specific codon usage is also considered.
Author Comment
This is a submission to PeerJ Computer Science for review.