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.
No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong
Qilu Normal University · Genelibs Bioinformatics Lab
750 Shunhua Rd, Jinan
2F, Bldg F, University Science Park
Tel: 0531-88819269
Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.
Business Email
E-mail: [email protected]