In protein engineering, generation of mutagenesis libraries is a key step to study the functions of mutants. To generate mutants with a desired composition of amino acids (AAs), a codon consisting of a mixture of nucleotides is widely applied. Several computational methods have been proposed to calculate a codon nucleotide composition for generating a given amino acid profile based on mathematical optimization. However, these previous methods need to manually tune weights of amino acids in objective functions, which are time-consuming and, more importantly, lack publicly available software implementations. Here, we develop CodonAdjust, a software to adjust a codon nucleotide composition for mimicking a given amino acid profile. We propose different options of CodonAdjust, which provide various customizations in practical scenarios such as setting a guaranteeing threshold for the frequencies of amino acids without any manual tasks. We demonstrate the capability of CodonAdjust in the experiments on the complementarity-determining regions (CDRs) of antibodies and T-cell receptors (TCRs) as well as millions of amino acid profiles from Pfam. These results suggest that CodonAdjust is a productive software for codon design and may accelerate library generation. CodonAdjust is freely available at https://github.com/tiffany-nguyen/CodonAdjust. Paper edited by Dr. Jeffery Saven, Board Member for PEDS.

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http://dx.doi.org/10.1093/protein/gzaa013DOI Listing

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