Codon Optimization for DNA Vaccines and Gene Therapy

Codon optimization enhances the effectiveness of DNA expression vectors used in DNA vaccination and gene therapy by increasing protein expression. Additionally certain nucleotide motifs have experimentally been shown to be immuno-stimulatory while certain others have been shown to be immuno-suppressive. In this paper, we present algorithms to locate all the possible occurrences of a given set of immunomodulatory motifs in the DNA expression vectors corresponding to a given amino acid sequence and maximize or minimize the number and the context of the immuno-modulatory motifs in the DNA expression vectors. The main contribution is to use multiple pattern matching algorithms to synthesize a DNA sequence for a given amino acid sequence and a graph theoretic approach for finding the longest weighted path in a directed graph that will maximize or minimize certain motifs as well as guarantee certain fitness factors of codon frequency usage for a particular species. This is achieved using O(n) time and storage resources compared to the brute force algorithm that might take exponential amount of resources, where n is the length of the amino acid sequence. Based on this, we develop a software tool that could help the researcher to codon optimize the DNA vector for a given species for higher protein expression in a heterologous system. Additionally, this software could also enable the researcher to analyze the content of CpG motifs in a given amino acid sequence and engineer CpG motifs for immuno-modulation.