title: GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences.
abstract: A new protein fold recognition method is described which is both fast and reliable. The method uses a traditional sequence alignment algorithm to generate alignments which are then evaluated by a method derived from threading techniques. As a final step, each threaded model is evaluated by a neural network in order to produce a single measure of confidence in the proposed prediction. The speed of the method, along with its sensitivity and very low false-positive rate makes it ideal for automatically predicting the structure of all the proteins in a translated bacterial genome (proteome). The method has been applied to the genome of Mycoplasma genitalium, and analysis of the results shows that as many as 46 % of the proteins derived from the predicted protein coding regions have a significant relationship to a protein of known structure. In some cases, however, only one domain of the protein can be predicted, giving a total coverage of 30 % when calculated as a fraction of the number of amino acid residues in the whole proteome.
authors: Department of Biological Sciences, University of Warwick, Coventry, CV4 7AL, UK. jones@globin.bio.warwick.ac.uk
authors: D T
authors: DT
authors: Jones
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D016678:Genome; D008969:Molecular Sequence Data; D016571:Neural Networks, Computer; D016366:Open Reading Frames; D011487:Protein Conformation; D017510:Protein Folding; D015203:Reproducibility of Results; D016415:Sequence Alignment / Q000379:methods*; D017386:Sequence Homology, Amino Acid