A pattern matching algorithm for codon optimization and CpG motif-engineering in DNA expression vectors.
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(2)) time, where n is the length of the amino acid sequence. Based on this, we develop a software tool.
Satya
Ravi Vijaya
RV
School of Engineering and Computer Science, University of Central Florida, Orlando, 32816, USA. rvijaya@cs.ucf.edu
Mukherjee
Amar
A
Ranga
Udaykumar
U
D000465:Algorithms; D020816:Amino Acid Motifs; D001185:Artificial Intelligence; D003062:Codon / Q000235:genetics*; D018899:CpG Islands / Q000235:genetics*; D015870:Gene Expression / Q000235:genetics; D005818:Genetic Engineering / Q000379:methods*; D005822:Genetic Vectors / Q000235:genetics*; D010363:Pattern Recognition, Automated / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software; D019444:Vaccines, DNA / Q000235:genetics
D003062:Codon; D019444:Vaccines, DNA