Author(s): Jones DT
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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. Copyright 1999 Academic Press.
This article was published in J Mol Biol
and referenced in Journal of Computer Science & Systems Biology