A pattern matching algorithm for codon optimization and CpG motif-engineering in DNA expression vectors

• Published in: 2nd IEEE Computer Society Bioinformatics Conference (CSB 2003) Vol. 2; pp. 294 - 305
• Main Authors: Satya, Ravi Vijaya, Mukherjee, Amar, Ranga, Udaykumar
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 2003
• Subjects: Algorithms; Amino Acid Motifs; Amino acids; Animals; Artificial Intelligence; Codon - genetics; CpG Islands - genetics; DNA; Gene Expression - genetics; Genetic Engineering - methods; Genetic Vectors - genetics; Humans; Immune system; Pathogens; Pattern matching; Pattern Recognition, Automated - methods; Proteins; Sequence Analysis, DNA - methods; Sequences; Software; Vaccines; Vaccines, DNA - genetics
• ISBN: 0769520006; 9780769520001
• ISSN: 1555-3930
• DOI: 10.1109/CSB.2003.1227330

Codon optimization enhances the efficiency 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 immuno-suppressive. In this paper, we present algorithms to locate a given set of immuno-modulatory 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. This is achieved using O(n/sup 2/) time, where n is the length of the amino acid sequence. Based on this, we develop a software tool.