1University of Central Florida, Orlando, FL, 32816, USA. E-mail:
2School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA. E-mail:
Identification of 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 are available. However, most of the software packages use a pre-defined threshold to select ordered or disordered residues. In many situations, users need to select 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 93 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.
