Bioinformatical Approaches to Unstructured/Disordered Proteins and Their Interactions

  • Bálint Mészáros
  • Zsuzsanna Dosztányi
  • Csaba Magyar
  • István Simon
Part of the Springer Series in Bio-/Neuroinformatics book series (SSBN, volume 1)


Intrinsically unstructured/disordered proteins (IUPs/IDPs) exist as highly flexible conformational ensembles without adopting a stable three-dimensional structure. Experimental and bioinformatical studies in the past two decades have shown that these proteins play a central role in various signaling and regulatory processes. Accordingly, their frequency in higher eukaryotes reaches high proportions and their malfunction can be connected to a wide variety of diseases. Recognizing the biological importance of these proteins motivated researchers to understand various aspects of disordered proteins and protein segments from the viewpoint of biochemistry, molecular biology and pharmacology. In general, IDPs are difficult to study experimentally because of the lack of a unique structure in the isolated form. Nevertheless, various bioinformatics tools developed over the last few years enable their identification and characterization using only the amino acid sequence. In this chapter — after a brief introduction to IDPs in general — we present a small survey of current methods aimed at identifying disordered proteins or protein segments, focusing on those that are publicly available as web servers. We also discuss in more detail approaches that predict disordered regions and specific regions involved in protein binding by modeling the physical background of protein disorder. Furthermore, we argue that the heterogeneity of disordered segments needs to be taken into account for a better understanding of protein disorder and the correct use and interpretation of the output of disorder prediction algorithms.


Binding Region Globular Protein Secondary Structure Prediction Linear Motif Bioinformatical Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Wright, P.E., Dyson, H.J.: Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm. J. Mol. Biol. 293(2), 321–331 (1999), doi:10.1006/jmbi.1999.3110, S0022-2836(99)93110-8 [pii]CrossRefGoogle Scholar
  2. 2.
    Dunker, A.K., Lawson, J.D., Brown, C.J., Williams, R.M., Romero, P., Oh, J.S., Oldfield, C.J., Campen, A.M., Ratliff, C.M., Hipps, K.W., Ausio, J., Nissen, M.S., Reeves, R., Kang, C., Kissinger, C.R., Bailey, R.W., Griswold, M.D., Chiu, W., Garner, E.C., Obradovic, Z.: Intrinsically disordered protein. J. Mol. Graph. Model. 19(1), 26–59 (2001), doi:S1093-3263(00)00138-8 [pii]CrossRefGoogle Scholar
  3. 3.
    Dyson, H.J., Wright, P.E.: Intrinsically unstructured proteins and their functions. Nat. Rev. Mol. Cell. Biol. 6(3), 197–208 (2005), doi:nrm1589, [pii] 10.1038/nrm1589 CrossRefGoogle Scholar
  4. 4.
    Tompa, P.: Intrinsically unstructured proteins. Trends Biochem. Sci. 27(10), 527–533 (2002), doi:S0968-0004(02)02169-2 [pii]CrossRefGoogle Scholar
  5. 5.
    Dunker, A.K., Obradovic, Z., Romero, P., Garner, E.C., Brown, C.J.: Intrinsic protein disorder in complete genomes. In: Genome Inform. Ser. Workshop Genome Inform., vol. 11, pp. 161–171 (2000)Google Scholar
  6. 6.
    Meszaros, B., Simon, I., Dosztanyi, Z.: Prediction of protein binding regions in disordered proteins. PLoS Comput. Biol. 5(5), e1000376 (2009), doi:10.1371/journal.pcbi.1000376 CrossRefGoogle Scholar
  7. 7.
    Ward, J.J., Sodhi, J.S., McGuffin, L.J., Buxton, B.F., Jones, D.T.: Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J. Mol. Biol. 337(3), 635–645 (2004), doi:10.1016/j.jmb.2004.02.002, S0022283604001482 [pii] CrossRefGoogle Scholar
  8. 8.
    Xie, H., Vucetic, S., Iakoucheva, L.M., Oldfield, C.J., Dunker, A.K., Uversky, V.N., Obradovic, Z.: Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 6(5), 1882–1898 (2007), doi:10.1021/pr060392uCrossRefGoogle Scholar
  9. 9.
    Tompa, P.: The interplay between structure and function in intrinsically unstructured proteins. FEBS Lett. 579(15), 3346–3354 (2005), doi:S0014-5793(05)00424-2, [pii] 10.1016/j.febslet.2005.03.072CrossRefGoogle Scholar
  10. 10.
    Galea, C.A., Wang, Y., Sivakolundu, S.G., Kriwacki, R.W.: Regulation of cell division by intrinsically unstructured proteins: intrinsic flexibility, modularity, and signaling conduits. Biochemistry 47(29), 7598–7609 (2008), doi:10.1021/bi8006803CrossRefGoogle Scholar
  11. 11.
    Uversky, V.N., Oldfield, C.J., Dunker, A.K.: Intrinsically disordered proteins in human diseases: introducing the D2 concept. Annu. Rev. Biophys. 37, 215–246 (2008), doi:10.1146/annurev.biophys.37.032807.125924 CrossRefGoogle Scholar
  12. 12.
    Cheng, Y., LeGall, T., Oldfield, C.J., Dunker, A.K., Uversky, V.N.: Abundance of intrinsic disorder in protein associated with cardiovascular disease. Biochemistry 45(35), 10448–10460 (2006), doi:10.1021/bi060981dCrossRefGoogle Scholar
  13. 13.
    Uversky, V.N.: Intrinsic disorder in proteins associated with neurodegenerative diseases. Front Biosci. 14, 5188–5238 (2009), doi:3594 [pii]CrossRefGoogle Scholar
  14. 14.
    Uversky, V.N., Oldfield, C.J., Midic, U., Xie, H., Xue, B., Vucetic, S., Iakoucheva, L.M., Obradovic, Z., Dunker, A.K.: Unfoldomics of human diseases: linking protein intrinsic disorder with diseases. BMC Genomics 10(suppl. 1), S7 (2009), doi:1471-2164-10-S1-S7, [pii] 10.1186/1471-2164-10-S1-S7CrossRefGoogle Scholar
  15. 15.
    Iakoucheva, L.M., Brown, C.J., Lawson, J.D., Obradovic, Z., Dunker, A.K.: Intrinsic disorder in cell-signaling and cancer-associated proteins. J. Mol. Biol. 323(3), 573–584 (2002), doi:S0022283602009695 [pii]CrossRefGoogle Scholar
  16. 16.
    Pajkos, M., Meszaros, B., Simon, I., Dosztanyi, Z.: Is there a biological cost of protein disorder? Analysis of cancer-associated mutations. Mol. Biosyst. 8(1), 296–307 (2012), doi:10.1039/c1mb05246bCrossRefGoogle Scholar
  17. 17.
    Cheng, Y., LeGall, T., Oldfield, C.J., Mueller, J.P., Van, Y.Y., Romero, P., Cortese, M.S., Uversky, V.N., Dunker, A.K.: Rational drug design via intrinsically disordered protein. Trends Biotechnol. 24(10), 435–442 (2006), doi:S0167-7799(06)00184-3, [pii] 10.1016/j.tibtech.2006.07.005zbMATHCrossRefGoogle Scholar
  18. 18.
    Metallo, S.J.: Intrinsically disordered proteins are potential drug targets. Curr. Opin. Chem. Biol. 14(4), 481–488 (2010), doi:S1367-5931(10)00074-8, [pii] 10.1016/j.cbpa.2010.06.169CrossRefGoogle Scholar
  19. 19.
    Uversky, V.N.: Natively unfolded proteins: a point where biology waits for physics. Protein Sci. 11(4), 739–756 (2002), doi:10.1110/ps.4210102CrossRefGoogle Scholar
  20. 20.
    Dyson, H.J., Wright, P.E.: Coupling of folding and binding for unstructured proteins. Curr. Opin. Struct. Biol. 12(1), 54–60 (2002), doi:S0959440X02002890 [pii]CrossRefGoogle Scholar
  21. 21.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E.: The Protein Data Bank. Nucleic Acids Res. 28(1), 235–242 (2000), doi:gkd090 [pii]CrossRefGoogle Scholar
  22. 22.
    Gunasekaran, K., Tsai, C.J., Nussinov, R.: Analysis of ordered and disordered protein complexes reveals structural features discriminating between stable and unstable monomers. J. Mol. Biol. 341(5), 1327–1341 (2004), doi:10.1016/j.jmb.2004.07.002, [pii] S0022-2836(04)00801-0 CrossRefGoogle Scholar
  23. 23.
    Meszaros, B., Tompa, P., Simon, I., Dosztanyi, Z.: Molecular principles of the interactions of dis-ordered proteins. J. Mol. Biol. 372(2), 549–561 (2007), doi:S0022-2836(07)00920-5, [pii] 10.1016/j.jmb.2007.07.004CrossRefGoogle Scholar
  24. 24.
    Uversky, V.N., Oldfield, C.J., Dunker, A.K.: Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling. J. Mol. Recognit. 18(5), 343–384 (2005), doi:10.1002/jmr.747CrossRefGoogle Scholar
  25. 25.
    Dosztanyi, Z., Chen, J., Dunker, A.K., Simon, I., Tompa, P.: Disorder and sequence repeats in hub proteins and their implications for network evolution. J. Proteome Res. 5(11), 2985–2995 (2006), doi:10.1021/pr060171o CrossRefGoogle Scholar
  26. 26.
    Bracken, C., Iakoucheva, L.M., Romero, P.R., Dunker, A.K.: Combining prediction, computation and experiment for the characterization of protein disorder. Curr. Opin. Struct. Biol. 14(5), 570–576 (2004), doi:S0959-440X(04)00137-X, [pii] 10.1016/ Scholar
  27. 27.
    Garner, E., Cannon, P., Romero, P., Obradovic, Z., Dunker, A.K.: Predicting Disordered Regions from Amino Acid Sequence: Common Themes Despite Differing Structural Characterization. In: Genome Inform. Ser. Workshop Genome Inform., vol. 9, pp. 201–213 (1998)Google Scholar
  28. 28.
    Li, X., Romero, P., Rani, M., Dunker, A.K., Obradovic, Z.: Predicting Protein Disorder for N-, C-, and Internal Regions. In: Genome Inform. Ser. Workshop Genome Inform., vol. 10, pp. 30–40 (1999)Google Scholar
  29. 29.
    Radivojac, P., Obradovic, Z., Smith, D.K., Zhu, G., Vucetic, S., Brown, C.J., Lawson, J.D., Dunker, A.K.: Protein flexibility and intrinsic disorder. Protein Sci. 13(1), 71–80 (2004), doi:10.1110/ps.03128904CrossRefGoogle Scholar
  30. 30.
    He, B., Wang, K., Liu, Y., Xue, B., Uversky, V.N., Dunker, A.K.: Predicting intrinsic disorder in proteins: an overview. Cell Res. 19(8), 929–949 (2009), doi:cr200987, [pii] 10.1038/cr.2009.87CrossRefGoogle Scholar
  31. 31.
    Wootton, J.C.: Non-globular domains in protein sequences: automated segmentation using complexity measures. Comput. Chem. 18(3), 269–285 (1994), doi:0097-8485(94)85023-2 [pii]zbMATHCrossRefGoogle Scholar
  32. 32.
    Wootton, J.C., Federhen, S.: Analysis of compositionally biased regions in sequence databases. Methods Enzymol. 266, 554–571 (1996)CrossRefGoogle Scholar
  33. 33.
    Romero, P., Obradovic, Z., Li, X., Garner, E.C., Brown, C.J., Dunker, A.K.: Sequence complexity of disordered protein. Proteins 42(1), 38–48 (2001), doi:10.1002/1097-0134(20010101)42:1<38::AID-PROT50>3.0.CO;2-3 [pii]CrossRefGoogle Scholar
  34. 34.
    Vucetic, S., Obradovic, Z., Vacic, V., Radivojac, P., Peng, K., Iakoucheva, L.M., Cortese, M.S., Lawson, J.D., Brown, C.J., Sikes, J.G., Newton, C.D., Dunker, A.K.: DisProt: a database of protein disorder. Bioinformatics 21(1), 137–140 (2005), doi:10.1093/bioinformatics/bth476bth476 [pii]CrossRefGoogle Scholar
  35. 35.
    Dutta, S., Burkhardt, K., Young, J., Swaminathan, G.J., Matsuura, T., Henrick, K., Nakamura, H., Berman, H.M.: Data deposition and annotation at the worldwide protein data bank. Mol. Biotechnol. 42(1), 1–13 (2009), doi:10.1007/s12033-008-9127-7CrossRefGoogle Scholar
  36. 36.
    Mohan, A., Uversky, V.N., Radivojac, P.: Influence of sequence changes and environment on intrinsically disordered proteins. PLoS Comput. Biol., e1000497 (2009), doi:10.1371/journal.pcbi.1000497Google Scholar
  37. 37.
    De Biasio, A., Guarnaccia, C., Popovic, M., Uversky, V.N., Pintar, A., Pongor, S.: Prevalence of intrinsic disorder in the intracellular region of human single-pass type I proteins: the case of the notch ligand Delta-4. J. Proteome Res. 7(6), 2496–2506 (2008), doi:10.1021/pr800063uCrossRefGoogle Scholar
  38. 38.
    Uversky, V.N., Gillespie, J.R., Fink, A.L.: Why are "natively unfolded" proteins unstructured under physiologic conditions? Proteins 41(3), 415–427 (2000), doi:10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.0.CO;2-7 [pii]CrossRefGoogle Scholar
  39. 39.
    Galzitskaya, O.V., Garbuzynskiy, S.O., Lobanov, M.Y.: FoldUnfold: web server for the prediction of disordered regions in protein chain. Bioinformatics 22(23), 2948–2949 (2006), doi:btl504, [pii] 10.1093/bioinformatics/btl504 CrossRefGoogle Scholar
  40. 40.
    Xie, Q., Arnold, G.E., Romero, P., Obradovic, Z., Garner, E., Dunker, A.K.: The Sequence Attribute Method for Determining Relationships Between Sequence and Protein Disorder. In: Genome Inform. Ser. Workshop Genome Inform., vol. 9, pp. 193–200 (1998)Google Scholar
  41. 41.
    Campen, A., Williams, R.M., Brown, C.J., Meng, J., Uversky, V.N., Dunker, A.K.: TOP-IDP-scale: a new amino acid scale measuring propensity for intrinsic disorder. Protein Pept. Lett. 15(9), 956–963 (2008)CrossRefGoogle Scholar
  42. 42.
    Linding, R., Russell, R.B., Neduva, V., Gibson, T.J.: GlobPlot: Exploring protein sequences for globularity and disorder. Nucleic Acids Res. 31(13), 3701–3708 (2003)CrossRefGoogle Scholar
  43. 43.
    Cheng, J., Sweredoski, M., Baldi, P.: Accurate prediction of protein disordered regions by mining protein structure. Data Mining and Klowledge Discovery 11, 213–222 (2005)MathSciNetCrossRefGoogle Scholar
  44. 44.
    Su, C.T., Chen, C.Y., Hsu, C.M.: iPDA: integrated protein disorder analyzer. Nucleic Acids Res. 35(Web Server Issue), W465–W472 (2007), doi:gkm353, [pii] 10.1093/nar/gkm353 CrossRefGoogle Scholar
  45. 45.
    Fuxreiter, M., Simon, I., Friedrich, P., Tompa, P.: Preformed structural elements feature in partner recognition by intrinsically unstructured proteins. J. Mol. Biol. 338(5), 1015–1026 (2004), doi:10.1016/j.jmb.2004.03.017, [pii] S0022283604003079 CrossRefGoogle Scholar
  46. 46.
    Suveges, D., Gaspari, Z., Toth, G., Nyitray, L.: Charged single alpha-helix: a versatile protein structural motif. Proteins 74(4), 905–916 (2009), doi:10.1002/prot.22183 CrossRefGoogle Scholar
  47. 47.
    Brown, C.J., Takayama, S., Campen, A.M., Vise, P., Marshall, T.W., Oldfield, C.J., Williams, C.J., Dunker, A.K.: Evolutionary rate heterogeneity in proteins with long disordered regions. J. Mol. Evol. 55(1), 104–110 (2002), doi:10.1007/s00239-001-2309-6 CrossRefGoogle Scholar
  48. 48.
    Daughdrill, G.W., Narayanaswami, P., Gilmore, S.H., Belczyk, A., Brown, C.J.: Dynamic behavior of an intrinsically unstructured linker domain is conserved in the face of negligible amino acid sequence conservation. J. Mol. Evol. 65(3), 277–288 (2007), doi:10.1007/s00239-007-9011-2 CrossRefGoogle Scholar
  49. 49.
    Peng, K., Radivojac, P., Vucetic, S., Dunker, A.K., Obradovic, Z.: Length-dependent prediction of protein intrinsic disorder. BMC Bioinformatics 7, 208 (2006), doi:1471-2105-7-208, [pii] 10.1186/1471-2105-7-208 CrossRefGoogle Scholar
  50. 50.
    Melamud, E., Moult, J.: Evaluation of disorder predictions in CASP5. Proteins 53(suppl. 6), 561–565 (2003), doi:10.1002/prot.10533CrossRefGoogle Scholar
  51. 51.
    Jin, Y., Dunbrack Jr., R.L.: Assessment of disorder predictions in CASP6. Proteins 61(suppl. 7), 167–175 (2005), doi:10.1002/prot.20734CrossRefGoogle Scholar
  52. 52.
    Bordoli, L., Kiefer, F., Schwede, T.: Assessment of disorder predictions in CASP7. Proteins 69(suppl. 8), 129–136 (2007), doi:10.1002/prot.21671CrossRefGoogle Scholar
  53. 53.
    Noivirt-Brik, O., Prilusky, J., Sussman, J.L.: Assessment of disorder predictions in CASP8. Proteins 77(suppl. 9), 210–216 (2009), doi:10.1002/prot.22586CrossRefGoogle Scholar
  54. 54.
    Monastyrskyy, B., Fidelis, K., Moult, J., Tramontano, A., Kryshtafovych, A.: Evaluation of disorder predictions in CASP9. Proteins 79(suppl. 10), 107–118 (2011), doi:10.1002/prot.23161CrossRefGoogle Scholar
  55. 55.
    Dosztanyi, Z., Sandor, M., Tompa, P., Simon, I.: Prediction of protein disorder at the domain level. Curr. Protein Pept. Sci. 8(2), 161–171 (2007)CrossRefGoogle Scholar
  56. 56.
    Schlessinger, A., Punta, M., Yachdav, G., Kajan, L., Rost, B.: Improved disorder prediction by combination of orthogonal approaches. PLoS One 4(2), e4433 (2009), doi:10.1371/journal.pone.0004433 CrossRefGoogle Scholar
  57. 57.
    Hirose, S., Shimizu, K., Kanai, S., Kuroda, Y., Noguchi, T.: POODLE-L: a two-level SVM prediction system for reliably predicting long disordered regions. Bioinformatics 23(16), 2046–2053 (2007), doi:btm302, [pii] 10.1093/bioinformatics/btm302 CrossRefGoogle Scholar
  58. 58.
    Dosztanyi, Z., Meszaros, B., Simon, I.: Bioinformatical approaches to characterize intrinsically disordered/unstructured proteins. Brief Bioinform. 11(2), 225–243 (2010), doi:bbp061, [pii] 10.1093/bib/bbp061CrossRefGoogle Scholar
  59. 59.
    Romero, Obradovic, Dunker, K.: Sequence Data Analysis for Long Disordered Regions Prediction in the Calcineurin Family. In: Genome Inform. Ser. Workshop Genome Inform., vol. 8, pp. 110–124 (1997)Google Scholar
  60. 60.
    Oldfield, C.J., Cheng, Y., Cortese, M.S., Romero, P., Uversky, V.N., Dunker, A.K.: Coupled folding and binding with alpha-helix-forming molecular recognition elements. Biochemistry 44(37), 12454–12470 (2005), doi:10.1021/bi050736e CrossRefGoogle Scholar
  61. 61.
    Cheng, Y., Oldfield, C.J., Meng, J., Romero, P., Uversky, V.N., Dunker, A.K.: Mining alpha-helix-forming molecular recognition features with cross species sequence alignments. Biochemistry 46(47), 13468–13477 (2007), doi:10.1021/bi7012273 CrossRefGoogle Scholar
  62. 62.
    Radivojac, P., Obradovic, Z., Brown, C.J., Dunker, A.K.: Prediction of boundaries between intrinsically ordered and disordered protein regions. In: Pac. Symp. Biocomput., pp. 216–227 (2003)Google Scholar
  63. 63.
    Linding, R., Jensen, L.J., Diella, F., Bork, P., Gibson, T.J., Russell, R.B.: Protein disorder prediction: implications for structural proteomics. Structure 11(11), 1453–1459 (2003), doi:S0969212603002351 [pii]CrossRefGoogle Scholar
  64. 64.
    Su, C.T., Chen, C.Y., Ou, Y.Y.: Protein disorder prediction by condensed PSSM considering propensity for order or disorder. BMC Bioinformatics 7, 319 (2006), doi:1471-2105-7-319, [pii] 10.1186/1471-2105-7-319 CrossRefGoogle Scholar
  65. 65.
    Schaffer, A.A., Aravind, L., Madden, T.L., Shavirin, S., Spouge, J.L., Wolf, Y.I., Koonin, E.V., Altschul, S.F.: Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements. Nucleic Acids Res. 29(14), 2994–3005 (2001)CrossRefGoogle Scholar
  66. 66.
    Ishida, T., Kinoshita, K.: PrDOS: prediction of disordered protein regions from amino acid sequence. Nucleic Acids Res. 35(Web Server Issue), W460–W464 (2007), doi:gkm363, [pii] 10.1093/nar/gkm363 CrossRefGoogle Scholar
  67. 67.
    Wang, L., Sauer, U.H.: OnD-CRF: predicting order and disorder in proteins using [corrected] conditional random fields. Bioinformatics 24(11), 1401–1402 (2008), doi:btn132, [pii] 10.1093/bioinformatics/btn132 CrossRefGoogle Scholar
  68. 68.
    MacCallum, R.: (date last accessed July 3, 2012 )
  69. 69.
    Obradovic, Z., Peng, K., Vucetic, S., Radivojac, P., Dunker, A.K.: Exploiting heterogeneous sequence properties improves prediction of protein disorder. Proteins 61(suppl. 7), 176–182 (2005), doi:10.1002/prot.20735CrossRefGoogle Scholar
  70. 70.
    Hirose, S., Shimizu, K., Inoue, N., Kanai, S., Noguchi, T.: Disordered region prediction by integrating POODLE series. In: CASP8 Proceedings 2008, pp. 14–15 (2008)Google Scholar
  71. 71.
    Bujnicki, J.M., Elofsson, A., Fischer, D., Rychlewski, L.: LiveBench-2: large-scale automated evaluation of protein structure prediction servers. Proteins (suppl. 5), 184–191 (2001), doi:10.1002/prot.10039 [pii]Google Scholar
  72. 72.
    Yang, Z.R., Thomson, R., McNeil, P., Esnouf, R.M.: RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins. Bioinformatics 21(16), 3369–3376 (2005), doi:bti534, [pii] 10.1093/bioinformatics/bti534 CrossRefGoogle Scholar
  73. 73.
    Dosztanyi, Z., Csizmok, V., Tompa, P., Simon, I.: The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. J. Mol. Biol. 347(4), 827–839 (2005), doi:S0022-2836(05)00129-4, [pii] 10.1016/j.jmb.2005.01.071 CrossRefGoogle Scholar
  74. 74.
    Prilusky, J., Felder, C.E., Zeev-Ben-Mordehai, T., Rydberg, E.H., Man, O., Beckmann, J.S., Silman, I., Suss-man, J.L.: FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically un-folded. Bioinformatics 21(16), 3435–3438 (2005), doi:bti537, [pii] 10.1093/bioinformatics/bti537 CrossRefGoogle Scholar
  75. 75.
    Thomas, P.D., Dill, K.A.: An iterative method for extracting energy-like quantities from protein structures. Proc. Natl. Acad. Sci. U S A 93(21), 11628–11633 (1996)CrossRefGoogle Scholar
  76. 76.
    Shortle, D.: Propensities, probabilities, and the Boltzmann hypothesis. Protein Sci. 12(6), 1298–1302 (2003), doi:10.1110/ps.0306903CrossRefGoogle Scholar
  77. 77.
    Dosztanyi, Z., Csizmok, V., Tompa, P., Simon, I.: IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 21(16), 3433–3434 (2005), doi:bti541, [pii] 10.1093/bioinformatics/bti541 CrossRefGoogle Scholar
  78. 78.
    Dosztanyi, Z., Meszaros, B., Simon, I.: ANCHOR: web server for predicting protein binding regions in disordered proteins. Bioinformatics 25(20), 2745–2746 (2009), doi:btp518, [pii] 10.1093/bioinformatics/btp518 CrossRefGoogle Scholar
  79. 79.
    Diella, F., Haslam, N., Chica, C., Budd, A., Michael, S., Brown, N.P., Trave, G., Gibson, T.J.: Understanding eukaryotic linear motifs and their role in cell signaling and regulation. Front Biosci. 13, 6580–6603 (2008), doi:3175 [pii]CrossRefGoogle Scholar
  80. 80.
    Sigrist, C.J., Cerutti, L., Hulo, N., Gattiker, A., Falquet, L., Pagni, M., Bairoch, A., Bucher, P.: PROSITE: a documented database using patterns and profiles as motif descriptors. Brief Bioinform. 3(3), 265–274 (2002)CrossRefGoogle Scholar
  81. 81.
    Neduva, V., Russell, R.B.: Linear motifs: evolutionary interaction switches. FEBS Lett. 579(15), 3342–3345 (2005), doi:S0014-5793(05)00461-8, [pii] 10.1016/j.febslet.2005.04.005 CrossRefGoogle Scholar
  82. 82.
    Stein, A., Aloy, P.: Contextual specificity in peptide-mediated protein interactions. PLoS One 3(7), e2524 (2008), doi:10.1371/journal.pone.0002524CrossRefGoogle Scholar
  83. 83.
    Dinkel, H., Michael, S., Weatheritt, R.J., Davey, N.E., Van Roey, K., Altenberg, B., Toedt, G., Uyar, B., Seiler, M., Budd, A., Jodicke, L., Dammert, M.A., Schroeter, C., Hammer, M., Schmidt, T., Jehl, P., McGuigan, C., Dymecka, M., Chica, C., Luck, K., Via, A., Chatr-Aryamontri, A., Haslam, N., Grebnev, G., Edwards, R.J., Steinmetz, M.O., Meiselbach, H., Diella, F., Gibson, T.J.: ELM–the database of eukaryotic linear motifs. Nucleic Acids Res. 40(Database Issue), D242–D251 (2012), doi:gkr1064, [pii] 10.1093/nar/gkr1064 CrossRefGoogle Scholar
  84. 84.
    Davey, N.E., Trave, G., Gibson, T.J.: How viruses hijack cell regulation. Trends Biochem. Sci. 36(3), 159–169 (2011), doi:S0968-0004(10)00200-8, [pii] 10.1016/j.tibs.2010.10.002 CrossRefGoogle Scholar
  85. 85.
    Davey, N.E., Edwards, R.J., Shields, D.C.: Estimation and efficient computation of the true probability of recurrence of short linear protein sequence motifs in unrelated proteins. BMC Bioinformatics 11, 14 (2010), doi:1471-2105-11-14, [pii] 10.1186/1471-2105-11-14 CrossRefGoogle Scholar
  86. 86.
    Gibson, T.J.: Cell regulation: determined to signal discrete cooperation. Trends Biochem. Sci. 34(10), 471–482 (2009), doi:S0968-0004(09)00142-X, [pii] 10.1016/j.tibs.2009.06.007 MathSciNetCrossRefGoogle Scholar
  87. 87.
    Stein, A., Pache, R.A., Bernado, P., Pons, M., Aloy, P.: Dynamic interactions of proteins in complex networks: a more structured view. FEBS J. 276(19), 5390–5405 (2009), doi:EJB7251, [pii] 10.1111/j.1742-4658.2009.07251.x CrossRefGoogle Scholar
  88. 88.
    Weatheritt, R.J., Luck, K., Petsalaki, E., Davey, N.E., Gibson, T.J.: The identification of short linear motif-mediated interfaces within the human interactome. Bioinformatics 28(7), 976–982 (2012), doi:bts072, [pii] 10.1093/bioinformatics/bts072 CrossRefGoogle Scholar
  89. 89.
    Lupas, A., Van Dyke, M., Stock, J.: Predicting coiled coils from protein sequences. Science 252(5009), 1162–1164 (1991), doi:252/5009/1162, [pii] 10.1126/science.252.5009.1162 CrossRefGoogle Scholar
  90. 90.
    Jones, D.T.: Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol. 292(2), 195–202 (1999), doi:10.1006/jmbi.1999.3091, [pii] S0022-2836(99)93091-7 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Bálint Mészáros
    • 1
  • Zsuzsanna Dosztányi
    • 1
  • Csaba Magyar
    • 1
  • István Simon
    • 1
  1. 1.Institute of EnzymologyRCNS, HASBudapestHungary

Personalised recommendations