CDF it all: Consensus prediction of intrinsically disordered proteins based on various cumulative distribution functions

Xue, Bin; Oldfield, Christopher J.; Dunker, A. Keith; Uversky, Vladimir N.

doi:10.1016/j.febslet.2009.03.070

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Volume 583, Issue 9 , Pages 1469-1474, 6 May 2009

CDF it all: Consensus prediction of intrinsically disordered proteins based on various cumulative distribution functions

Edited by Robert B. Russell

Bin Xue
- Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 410 W. 10th Street, HS 5009, Indianapolis, IN 46202, USA
- Institute for Intrinsically Disordered Protein Research, Indiana University School of Medicine, Indianapolis, IN 46202, USA
Christopher J. Oldfield
- Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 410 W. 10th Street, HS 5009, Indianapolis, IN 46202, USA
A. Keith Dunker
- Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 410 W. 10th Street, HS 5009, Indianapolis, IN 46202, USA
- Institute for Intrinsically Disordered Protein Research, Indiana University School of Medicine, Indianapolis, IN 46202, USA
Vladimir N. Uversky
- Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 410 W. 10th Street, HS 5009, Indianapolis, IN 46202, USA
- Institute for Intrinsically Disordered Protein Research, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Institute for Biological Instrumentation, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia
- Corresponding author. Address: Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 410 W. 10th Street, HS 5009, Indianapolis, IN 46202, USA. Fax: +1 317 278 9217.

Received 28 January 2009; received in revised form 18 March 2009; accepted 27 March 2009. published online 06 April 2009.

Abstract

Many biologically active proteins are intrinsically disordered. A reasonable understanding of the disorder status of these proteins may be beneficial for better understanding of their structures and functions. The disorder contents of disordered proteins vary dramatically, with two extremes being fully ordered and fully disordered proteins. Often, it is necessary to perform a binary classification and classify a whole protein as ordered or disordered. Here, an improved error estimation technique was applied to develop the cumulative distribution function (CDF) algorithms for several established disorder predictors. A consensus binary predictor, based on the artificial neural networks, NN-CDF, was developed by using output of the individual CDFs. The consensus method outperforms the individual predictors by 4–5% in the averaged accuracy.

Abbreviations: IDP, intrinsically disordered protein, IDR, intrinsically disordered region, CDF, cumulative distribution function, PONDR, predictor of natural disordered regions, PDD, partially disordered dataset