This article is part of the supplement: The 2007 International Conference on Bioinformatics & Computational Biology (BIOCOMP'07)
Protein disorder prediction at multiple levels of sensitivity and specificity
1 School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA
2 Harvard University, PO Box 40088, Cambridge, Massachusetts 02140-0888, USA
3 Computer Science Department and Informatics Institute, University of Missouri, Columbia, MO 65211, USA
BMC Genomics 2008, 9(Suppl 1):S9 doi:10.1186/1471-2164-9-S1-S9Published: 20 March 2008
Many protein regions and some entire proteins have no definite tertiary structure, existing instead as dynamic, disorder ensembles under different physiochemical circumstances. Identification of these protein disorder regions is important for protein production, protein structure prediction and determination, and protein function annotation. A number of different disorder prediction software and web services have been developed since the first predictor was designed by Dunker's lab in 1997. However, most of the software packages use a pre-defined threshold to select ordered or disordered residues. In many situations, users need to choose ordered or disordered residues at different sensitivity and specificity levels.
Here we benchmark a state of the art disorder predictor, DISpro, on a large protein disorder dataset created from Protein Data Bank and systematically evaluate the relationship of sensitivity and specificity. Also, we extend its functionality to allow users to trade off specificity and sensitivity by setting different decision thresholds. Moreover, we compare DISpro with seven other automated disorder predictors on the 95 protein targets used in the seventh edition of Critical Assessment of Techniques for Protein Structure Prediction (CASP7). DISpro is ranked as one of the best predictors.
The evaluation and extension of DISpro make it a more valuable and useful tool for structural and functional genomics.