MFDp2: Accurate predictor of disorder in proteins by fusion of disorder probabilities, content and profiles

Intrinsically Disordered Proteins
Marcin J MiziantyLukasz Kurgan

Abstract

Intrinsically disordered proteins (IDPs) are either entirely disordered or contain disordered regions in their native state. IDPs were found to be abundant in complex organisms and implicated in numerous cellular processes. Experimental annotation of disorder lags behind the rapidly growing sizes of the protein databases, and thus computational methods are used to close this gap and to investigate the disorder. MFDp2 is a novel content-rich and user-friendly web server for sequence-based prediction of protein disorder that builds upon our residue-level disorder predictor MFDp and chain-level disorder content predictor DisCon. It applies novel post-processing filters and uses sequence alignment to improve predictive quality. Using a new benchmark data set, which has reduced sequence identity to corresponding training data sets, MFDp2 is shown to provide competitive predictive quality when compared with MFDp and a comprehensive set of 13 other state-of-the-art predictors, including publicly available versions of the top predictors from CASP9. Our server obtains the highest Mathews Correlation Coefficient (MCC) and the second best Area Under the receiver operating characteristic Curve (AUC). In addition to the disorder predictions...Continue Reading

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Citations

Oct 3, 2017·Bioinformatics·Marco NecciSilvio C E Tosatto
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Software Mentioned

DISOPRED
PrDos
no blast
ESpritz
SPINE3
PSI
CSpritz
MFDp
DISOPRED2
SVM SHORT

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