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2008

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

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SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
Background: Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results: SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predic...
Lukasz A. Kurgan, Krzysztof J. Cios, Ke Chen 0003
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Lukasz A. Kurgan, Krzysztof J. Cios, Ke Chen 0003
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