Integrated Servers for Structure-Informed Function Prediction

No single method for predicting a protein's function from its three-dimensional structure is perfect; some methods work well in some cases, whereas other methods perform better in others. Consequently, it makes sense to apply a number of different predictive methods to a given protein structure and obtain either a consensus or the most likely prediction from them all. In this chapter we describe two web servers, ProKnow ( and ProFunc (, that use a cocktail of methods for predicting function from 3D structure.


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  1. Altschul SF, Madden TL, Schaffer AA, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389–3402PubMedCrossRefGoogle Scholar
  2. Anantharaman V, Aravind L, Koonin EV (2003) Emergence of diverse biochemical activities in evolutionarily conserved structural scaffolds of proteins Curr Opin Chem Biol 7:12–20PubMedCrossRefGoogle Scholar
  3. Aravind L, Anantharaman V, Balaji S, et al. (2005) The many faces of the helix-turn-helix domain: transcription regulation and beyond. FEMS Microbiol Rev 29:231–262PubMedCrossRefGoogle Scholar
  4. Barker JA, Thornton JM (2003) An algorithm for constraint-based structural template matching: application to 3D templates with statistical analysis. Bioinformatics 19:1644–1649PubMedCrossRefGoogle Scholar
  5. Berrondo M, Ostermeier M, Gray JJ (2008) Structure prediction of domain insertion proteins from structures of individual domains. Structure 16:513–527PubMedCrossRefGoogle Scholar
  6. Bowers PM, Pellegrini M, Thompson MJ, et al. (2004) Prolinks: a database of protein functional linkages derived from coevolution. Genome Biol 5:R35PubMedCrossRefGoogle Scholar
  7. Bryson K, McGuffin LJ, Marsden RL, et al. (2005) Protein structure prediction servers at University College London. Nucleic Acids Res 33:W36–W38PubMedCrossRefGoogle Scholar
  8. Camon E, Magrane M, Barrell D, et al. (2004) The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology. Nucleic Acids Res 32:D262–D266PubMedCrossRefGoogle Scholar
  9. Carugo O (2006) Rapid methods for comparing protein structures and scanning structure databases. Curr. Bioinformatics 1:75–83CrossRefGoogle Scholar
  10. Cuff ME, Li H, Moy S, et al. (2007) Crystal structure of an acetyltransferase protein from Vibrio cholerae strain N16961. Proteins 69:422–427PubMedCrossRefGoogle Scholar
  11. Fischer D, Eisenberg D (1997) Assigning folds to the proteins encoded by the genome of Mycoplasma genitalium. Proc. Natl Acad Sci USA 94:11929–11934PubMedCrossRefGoogle Scholar
  12. Glaser F, Pupko T, Paz I, et al. (2003) ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information. Bioinformatics 19:163–164PubMedCrossRefGoogle Scholar
  13. Hermann JC, Ghanem E, Li Y, et al. (2006) Predicting substrates by docking high-energy intermediates to enzyme structures. J. Am. Chem. Soc. 128:15882–15891PubMedCrossRefGoogle Scholar
  14. Holm L, Sander C (1998) Touring the fold space with DALI/FSSP. Nucleic Acids Res. 26:316–319PubMedCrossRefGoogle Scholar
  15. Hulo N, Sigrist CJ, Le Saux V, et al. (2004) Recent improvements to the PROSITE database. Nucleic Acids Res. 32:D134–D137PubMedCrossRefGoogle Scholar
  16. Hutchinson EG, Thornton JM (1990) HERA: a program to draw schematic diagrams of protein secondary structures. Proteins 8:203–212PubMedCrossRefGoogle Scholar
  17. Jeffery CJ (1999) Moonlighting proteins. Trends Biochem. Sci. 24:8–11PubMedCrossRefGoogle Scholar
  18. Jones S, Barker JA, Nobeli I, et al. (2003) Using structural motif templates to identify proteins with DNA binding function. Nucleic Acids Res. 31:2811–2823PubMedCrossRefGoogle Scholar
  19. Kim SH, Shin DH, Choi IG, et al. (2003) Structure-based functional inference in structural genomics. J. Struct. Funct. Genomics 4:129–135PubMedCrossRefGoogle Scholar
  20. Kleywegt GJ (1999) Recognition of spatial motifs in protein structures. J. Mol. Biol. 285:1887–1897PubMedCrossRefGoogle Scholar
  21. Krissinel E, Henrick K (2004) Secondary-structure matching (SSM), a new tool for fast protein structure alignment in three dimensions. Acta Crystallogr. D60:2256–2268Google Scholar
  22. Laskowski RA (1995) SURFNET: a program for visualizing molecular surfaces, cavities and intermolecular interactions. J. Mol. Graph. 13:323–330PubMedCrossRefGoogle Scholar
  23. Laskowski RA, Luscombe NM, Swindells MB, et al. (1996) Protein clefts in molecular recognition and function. Protein Science 5:2438–2452PubMedGoogle Scholar
  24. Laskowski RA, Chistyakov VV, Thornton JM (2005a) PDBsum more: new summaries and analyses of the known 3D structures of proteins and nucleic acids. Nucleic Acids Res. 33: D266–D268CrossRefGoogle Scholar
  25. Laskowski RA, Watson JD, Thornton JM (2005b) ProFunc: a server for predicting protein function from 3D structure. Nucleic Acids Res. 33:W89–W93CrossRefGoogle Scholar
  26. Laskowski RA, Watson JD, Thornton JM (2005c) Protein function prediction using local 3D templates. J. Mol. Biol. 352:614–626CrossRefGoogle Scholar
  27. Lichtarge O, Sowa ME (2002) Evolutionary predictions of binding surfaces and interactions. Curr. Opin. Struct. Biol. 12:21–27PubMedCrossRefGoogle Scholar
  28. Madabushi S, Yao H, Marsh M, et al. (2002) Structural clusters of evolutionary trace residues are statistically significant and common in proteins. J. Mol. Biol. 316:139–154PubMedCrossRefGoogle Scholar
  29. Mallick P, Weiss R, Eisenberg D (2002) The directional atomic solvation energy: an atom-based potential for the assignment of protein sequences to known folds. Proc. Natl. Acad. Sci. USA 99:16041–16046PubMedCrossRefGoogle Scholar
  30. Moult J (2005) A decade of CASP: progress, bottlenecks and prognosis in protein structure prediction. Curr. Opin. Struct. Biol. 15:285–289PubMedCrossRefGoogle Scholar
  31. Nagano N, Hutchinson EG, Thornton JM (1999) Barrel structures in proteins: automatic identification and classification including a sequence analysis of TIM barrels. Prot. Sci. 8:2072–2084CrossRefGoogle Scholar
  32. Novotny M, Madsen D, Kleywegt GJ (2004) Evaluation of protein fold comparison servers. Proteins 54:260–270PubMedCrossRefGoogle Scholar
  33. Orengo CA, Jones DT, Thornton JM (1994). Protein superfamilies and domain superfolds. Nature 372:631–634PubMedCrossRefGoogle Scholar
  34. Pal D, Eisenberg D (2005) Inference of protein function from protein structure. Structure 13:121–130PubMedCrossRefGoogle Scholar
  35. Pearson WR (1998) Empirical statistical estimates for sequence similarity searches. J. Mol. Biol. 276:71–84PubMedCrossRefGoogle Scholar
  36. Porter CT, Bartlett GJ, Thornton JM (2004) The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data. Nucleic Acids Res. 32: D129–D133PubMedCrossRefGoogle Scholar
  37. Quevillon E, Silventoinen V, Pillai S, et al. (2005) InterProScan: protein domains identifier. Nucleic Acids Res. 33:W116–W120PubMedCrossRefGoogle Scholar
  38. Rigden DJ (2006) Understanding the cell in terms of structure and function: insights from structural genomics. Curr. Opin. Biotechnol. 17:457–464PubMedCrossRefGoogle Scholar
  39. Sayle RA, Milner-White EJ (1995) RASMOL: biomolecular graphics for all. Trends Biochem. Sci. 20:374–376PubMedCrossRefGoogle Scholar
  40. Shanahan HP, Garcia MA, Jones S, et al. (2004) Identifying DNA-binding proteins using structural motifs and the electrostatic potential. Nucleic Acids Res. 32:4732–41PubMedCrossRefGoogle Scholar
  41. Shrager J (2003) The fiction of function. Bioinformatics 19:1934–1936PubMedCrossRefGoogle Scholar
  42. Sierk ML, Pearson WR (2004) Sensitivity and selectivity in protein structure comparison. Protein Sci. 13:773–785PubMedCrossRefGoogle Scholar
  43. Stamm S, Ben-Ari S, Rafalska I, et al. (2005) Function of alternative splicing. Gene 344:1–20PubMedCrossRefGoogle Scholar
  44. The Gene Ontology Consortium (2000) Gene Ontology tool for the unification of biology. Nat. Genet. 25:25–29CrossRefGoogle Scholar
  45. Watson JD, Milner-White EJ (2002a) A novel main-chain anion-binding site in proteins: the nest. A particular combination of phi,psi values in successive residues gives rise to anion-binding sites that occur commonly and are found often at functionally important regions. J. Mol. Biol. 315:171–182CrossRefGoogle Scholar
  46. Watson JD, Milner-White EJ (2002b) The conformations of polypeptide chains where the main-chain parts of successive residues are enantiomeric. Their occurrence in cation and anion-bind-ing regions of proteins. J. Mol. Biol. 315:183–191CrossRefGoogle Scholar
  47. Watson JD, Laskowski RA, Thornton JM (2005) Predicting protein function from sequence and structural data. Curr. Opin. Struct. Biol. 15:275–284PubMedCrossRefGoogle Scholar
  48. Watson JD, Sanderson S, Ezersky A, et al. (2007) Towards fully automated structure-based function prediction in structural genomics: a case study. J. Mol. Biol. 367:1511–1522PubMedCrossRefGoogle Scholar
  49. Wollacott AM, Zanghellini A, Murphy P, et al. (2007) Prediction of structures of multidomain proteins from structures of the individual domains. Protein Sci. 16:165–175PubMedCrossRefGoogle Scholar
  50. Xenarios I, Salwinski L, Duan XJ, et al. (2002) DIP, database of interacting proteins: a research tool for studying cellular networks of protein interactions. Nucleic Acids Res. 30:303–305PubMedCrossRefGoogle Scholar
  51. Yakunin AF, Yee AA, Savchenko A, et al. (2004) Structural proteomics: a tool for genome annotation. Curr. Opin. Chem. Biol. 8:42–48PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media B.V 2009

Authors and Affiliations

  1. 1.European Bioinformatics InstituteWellcome Trust Genome CampusCambridgeUK

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