Identifying Silent Mutations for the Introduction of Restriction Sites in Open Reading Frames

For many applications in molecular biology, restriction sites need to be engineered into an open reading frame (ORF), a part of the genetic material that codes for a protein. Importantly, silent mutations need to be performed because only these do not alter the amino acid sequence of the protein. However, finding such silent mutations is a very timeconsuming process. We have developed a program which recognizes all silent mutations in an open reading frame (ORF) that each lead to a new restriction site. Our program uses python technologies comprising web crawlers and data analysis libraries to deduce the amino acid sequence coded by an ORF and convert the ORF nucleotide sequence into the amino acid single letter sequence. In doing so, reverse translation back into the nucleotide sequence allows the consideration of all possible nucleotide sequences coding for the same amino acid sequence, which are then compared with the restriction recognition sites of commercially available restriction enzymes, such as from New England Biolabs (e.g., https://www.neb.com/). This allows the identification of restriction sites that can be engineered via silent mutations within the provided DNA input sequences. The output is presented in a user-friendly tabular format that can be examined or downloaded (as a CSV file) for ongoing evaluations.