Secondary structure computer prediction of the poliovirus 5' non-coding region is improved by a genetic algorithm

• Published in: Bioinformatics Vol. 13; no. 1; pp. 1 - 12
• Main Authors: Currey, Kathleen M., Shapiro, Bruce A.
• Format: Journal Article
• Language: English
• Published: Washington, DC Oxford University Press 01.02.1997; Oxford
• Subjects: Algorithms; Biological and medical sciences; Computer Simulation; Fundamental and applied biological sciences. Psychology; General aspects; Genetics; Genome, Viral; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Microbiology; Models, Genetic; Molecular Structure; Nucleic Acid Conformation; Poliovirus - genetics; RNA, Viral - chemistry; RNA, Viral - genetics; Software; Virology; 5' terminal-Sequence; RNA; Picornaviridae; Prediction; Non coding sequence; Enterovirus; Poliovirus; Secondary structure; Virus; Genetic algorithm; Computerized processing; Models; Property structure relationship; Mutation; Structural analysis
• ISSN: 1367-4803; 0266-7061; 1460-2059; 1460-2059
• DOI: 10.1093/bioinformatics/13.1.1

Comparison of the secondary structure of the 5' non-coding region of poliovirus 3 RNA derived from the genetic algorithm with the model of Skinner et al. (J. Mol. Biol., 207, 379–392, 1989) demonstrates many of the confirmed structural elements. The genetic algorithm (Shapiro and Navetta, J. Supercomput., 8, 195–201, 1994) generates a population of all possible stems, then mixes, combines, and recombines these stems in multiple iterations on a massively parallel computer, ultimately selecting a most fit structure based on its energy. The secondary structure of the region containing the determinants of neurovirulence was better predicted using the genetic algorithm, whereas the dynamic programing algorithm (Zuker, Science, 244, 48–52, 1989) required phylogenetic comparative sequence analysis to arrive at the correct conclusion. In addition, artificial mutations were introduced throughout this region of the genome and although rearrangements in structure may occur, many structures persisted, suggesting that the given structures thus selected may have evolved to withstand isolated mutations. The genetic algorithm-derived structure for the 5' non-coding region compares favorably with the biological data and functions previously described, and contains all of the ‘persistent’ structures, suggesting also that the persistence factor may be an aid to validating structures.