DISOPRED3: Precise disordered region predictions with annotated protein-binding activity

Bioinformatics

Volumn 31, Issue 6, 2015, Pages 857-863

  Jones, David T ^a   Cozzetto, Domenico ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EUKARYOTA;

INTRINSICALLY DISORDERED PROTEIN; PROTEIN BINDING;

ARTIFICIAL NEURAL NETWORK; BINDING SITE; BIOLOGY; CHEMISTRY; FACTUAL DATABASE; METABOLISM; MOLECULAR GENETICS; PROTEIN DOMAIN; SOFTWARE;

BINDING SITES; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; INTRINSICALLY DISORDERED PROTEINS; MOLECULAR SEQUENCE ANNOTATION; NEURAL NETWORKS (COMPUTER); PROTEIN BINDING; PROTEIN INTERACTION DOMAINS AND MOTIFS; SOFTWARE;

EID: 84925251625     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btu744     Document Type: Article

References (43)

1. Altschul, S.F. et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res., 25, 3389-3402.
2. Berman, H.M. et al. (2000) The Protein Data Bank. Nucleic Acids Res., 28, 235-242.
3. Buljan, M. et al. (2013) Alternative splicing of intrinsically disordered regions and rewiring of protein interactions. Curr. Opin. Struct. Biol., 23, 443-450.
4. Chang, C.-C. and Lin, C.-J. (2011) LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol., 2, 1-27.
5. Cozzetto, D. and Jones, D.T. (2013) The contribution of intrinsic disorder prediction to the elucidation of protein function. Curr. Opin. Struct. Biol., 23, 467-472.
6. DeLong, E.R. et al. (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics, 44, 837-845.
7. Deng, X. et al. (2012) A comprehensive overview of computational protein disorder prediction methods. Mol. Biosyst., 8, 114-121.
8. Disfani F.M. et al. (2012) MoRFpred, a computational tool for sequencebased prediction and characterization of short disorder-to-order transitioning binding regions in proteins. Bioinformatics, 28, i75-i83.
9. Dosztanyi, Z. et al. (2005) The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. J. Mol. Biol., 347, 827-839.
10. Eickholt, J. and Cheng, J. (2013) DNdisorder: predicting protein disorder using boosting and deep networks. BMC Bioinformatics, 14, 88.
11. Fang, C. et al. (2013) MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation. BMC Bioinformatics, 14, 300.
12. Hirose, S. et al. (2007) POODLE-L: a two-level SVM prediction system for reliably predicting long disordered regions. Bioinformatics, 23, 2046-2053.
13. Ishida, T. and Kinoshita, K. (2007) PrDOS: prediction of disordered protein regions from amino acid sequence. Nucleic Acids Res., 35, W460-W464.
14. Ishida, T. and Kinoshita, K. (2008) Prediction of disordered regions in proteins based on the meta approach. Bioinformatics, 24, 1344-1348.
15. Jones, D.T. and Ward, J.J. (2003) Prediction of disordered regions in proteins from position specific score matrices. Proteins, 53 (Suppl. 6), 573-578.
16. Khan, W. et al. (2013) Predicting binding within disordered protein regions to structurally characterised peptide-binding domains. PLoS One, 8, e72838.
17. Kozlowski, L.P. and Bujnicki, J.M. (2012) MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins. BMC Bioinformatics, 13, 111.
18. Linding, R. et al. (2003) GlobPlot: Exploring protein sequences for globularity and disorder. Nucleic Acids Res., 31, 3701-3708.
19. Liu, J. and Rost, B. (2003) NORSp: predictions of long regions without regular secondary structure. Nucleic Acids Res., 31, 3833-3835.
20. Lobley, A. et al. (2007) Inferring function using patterns of native disorder in proteins. PLoS Comput. Biol., 3, e162.
21. Melamud, E. and Moult, J. (2003) Evaluation of disorder predictions in CASP5. Proteins, 53 (Suppl 6), 561-565.
22. Meszaros, B. et al. (2009) Prediction of protein binding regions in disordered proteins. PLoS Comput. Biol., 5, e1000376.
23. Minneci, F. et al. (2013) FFPred 2.0: improved homology-independent prediction of gene ontology terms for eukaryotic protein sequences. PLoS One, 8, e63754.
24. Monastyrskyy, B. et al. (2011) Evaluation of disorder predictions in CASP9. Proteins, 79 (Suppl 10), 107-118.
25. Monastyrskyy, B. et al. (2014) Assessment of protein disorder region predictions in CASP10. Proteins, 82 (Suppl 2), 127-137.
26. Noivirt-Brik, O. et al. (2009) Assessment of disorder predictions in CASP8. Proteins, 77 (Suppl 9), 210-216.
27. Orosz, F. and Ovadi, J. (2011) Proteins without 3D structure: definition, detection and beyond. Bioinformatics, 27, 1449-1454.
28. Perkins, J.R. et al. (2010) Transient protein-protein interactions: structural, functional, and network properties. Structure, 18, 1233-1243.
29. Prilusky, J. et al. (2005) FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics, 21, 3435-3438.
30. R Core Team. (2012) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
31. Robin, X. et al. (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics, 12, 77.
32. Schlessinger, A. et al. (2009) Improved disorder prediction by combination of orthogonal approaches. PLoS One, 4, e4433.
33. Shimizu, K. et al. (2007a) POODLE-S: web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix. Bioinformatics, 23, 2337-2338.
34. Shimizu, K. et al. (2007b) Predicting mostly disordered proteins by using structure-unknown protein data. BMC Bioinformatics, 8, 78.
35. Sickmeier, M. et al. (2007) DisProt: the database of disordered proteins. Nucleic Acids Res, 35, D786-D793.
36. Sillitoe, I. et al. (2013) New functional families (FunFams) in CATH to improve the mapping of conserved functional sites to 3D structures. Nucleic Acids Res., 41, D490-D498.
37. Suzek, B.E. et al. (2007) UniRef: comprehensive and non-redundant UniProt reference clusters. Bioinformatics, 23, 1282-1288.
38. UniProt Consortium. (2014) Activities at the Universal Protein Resource (UniProt). Nucleic Acids Res., 42, D191-D198.
39. Velankar, S. et al. (2013) SIFTS: Structure Integration with Function, Taxonomy and Sequences resource. Nucleic Acids Res, 41, D483-D489.
40. Wang, G. and Dunbrack, R.L. Jr. (2005) PISCES: recent improvements to a PDB sequence culling server. Nucleic Acids Res., 33, W94-W98.
41. Wang, X. et al. (2010) A large intrinsically disordered region in SKIP and its disorder-order transition induced by PPIL1 binding revealed by NMR. J. Biol. Chem., 285, 4951-4963.
42. Ward, J.J. et al. (2004) Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J. Mol. Biol., 337, 635-645.
43. Zemla, A. (2003) LGA: a method for finding 3D similarities in protein structures. Nucleic Acids Res., 31, 3370-3374.