PreDisorder: ab initio sequence-based prediction of protein disordered regions

BackgroundDisordered regions are segments of the protein chain which do not adopt stable structures. Such segments are often of interest because they have a close relationship with protein expression and functionality. As such, protein disorder prediction is important for protein structure prediction, structure determination and function annotation.ResultsThis paper presents our protein disorder prediction server, PreDisorder. It is based on our ab initio prediction method (MULTICOM-CMFR) which, along with our meta (or consensus) prediction method (MULTICOM), was recently ranked among the top disorder predictors in the eighth edition of the Critical Assessment of Techniques for Protein Structure Prediction (CASP8). We systematically benchmarked PreDisorder along with 26 other protein disorder predictors on the CASP8 data set and assessed its accuracy using a number of measures. The results show that it compared favourably with other ab initio methods and its performance is comparable to that of the best meta and clustering methods.ConclusionPreDisorder is a fast and reliable server which can be used to predict protein disordered regions on genomic scale. It is available at http://casp.rnet.missouri.edu/predisorder.html.

[1]  John Moult,et al.  Evaluation of disorder predictions in CASP5 , 2003, Proteins.

[2]  Pierre Baldi,et al.  Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles , 2002, Proteins.

[3]  Arne Elofsson,et al.  3D-Jury: A Simple Approach to Improve Protein Structure Predictions , 2003, Bioinform..

[4]  Pierre Baldi,et al.  SCRATCH: a protein structure and structural feature prediction server , 2005, Nucleic Acids Res..

[5]  H. Dyson,et al.  Intrinsically unstructured proteins and their functions , 2005, Nature Reviews Molecular Cell Biology.

[6]  Roland L. Dunbrack,et al.  Assessment of disorder predictions in CASP6 , 2005, Proteins.

[7]  Bernard F. Buxton,et al.  The DISOPRED server for the prediction of protein disorder , 2004, Bioinform..

[8]  J. S. Sodhi,et al.  Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. , 2004, Journal of molecular biology.

[9]  Torsten Schwede,et al.  Assessment of disorder predictions in CASP7 , 2007, Proteins.

[10]  Liam J. McGuffin,et al.  Intrinsic disorder prediction from the analysis of multiple protein fold recognition models , 2008, Bioinform..

[11]  Predrag Radivojac,et al.  Influence of Sequence Changes and Environment on Intrinsically Disordered Proteins , 2009, PLoS Comput. Biol..

[12]  Zheng Rong Yang,et al.  RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins , 2005, Bioinform..

[13]  Leszek Rychlewski,et al.  Evaluation of 3D-Jury on CASP7 models , 2007, BMC Bioinformatics.

[14]  P. Radivojac,et al.  PROTEINS: Structure, Function, and Bioinformatics Suppl 7:176–182 (2005) Exploiting Heterogeneous Sequence Properties Improves Prediction of Protein Disorder , 2022 .

[15]  Jianlin Cheng,et al.  Protein disorder prediction at multiple levels of sensitivity and specificity , 2008, BMC Genomics.

[16]  Zoran Obradovic,et al.  The protein trinity—linking function and disorder , 2001, Nature Biotechnology.

[17]  A Keith Dunker,et al.  Intrinsic disorder and protein function. , 2002, Biochemistry.

[18]  Pierre Baldi,et al.  Accurate Prediction of Protein Disordered Regions by Mining Protein Structure Data , 2005, Data Mining and Knowledge Discovery.

[19]  Jack Y. Yang,et al.  IUP: Intrinsically Unstructured Protein predictor - A software tool for analyzing polypeptide sequences , 2006, Sixth IEEE Symposium on BioInformatics and BioEngineering (BIBE'06).

[20]  T JonesDavid,et al.  The DISOPRED server for the prediction of protein disorder , 2004 .

[21]  Anne Poupon,et al.  Prediction of unfolded segments in a protein sequence based on amino acid composition , 2005, Bioinform..

[22]  Yu-Yen Ou,et al.  Protein disorder prediction by condensed PSSM considering propensity for order or disorder , 2006, BMC Bioinformatics.

[23]  Sonia Longhi,et al.  A practical overview of protein disorder prediction methods , 2006, Proteins.

[24]  Jaime Prilusky,et al.  Assessment of disorder predictions in CASP8 , 2009, Proteins.

[25]  Baldomero Oliva,et al.  PIANA: protein interactions and network analysis , 2006, Bioinform..

[26]  P. Baldi,et al.  Prediction of coordination number and relative solvent accessibility in proteins , 2002, Proteins.

[27]  Zoran Obradovic,et al.  Length-dependent prediction of protein intrinsic disorder , 2006, BMC Bioinformatics.

[28]  P. Tompa.  Intrinsically unstructured proteins. , 2002, Trends in biochemical sciences.

[29]  Sonia Longhi,et al.  Assessing protein disorder and induced folding , 2005, Proteins.

[30]  Marc S. Cortese,et al.  Comparing and combining predictors of mostly disordered proteins. , 2005, Biochemistry.

[31]  Silvio C. E. Tosatto,et al.  Spritz: a server for the prediction of intrinsically disordered regions in protein sequences using kernel machines , 2006, Nucleic Acids Res..