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270 R.A. LaskowskiReferencesAltschul SF, Madden TL, Schaffer AA, et al. (1997) Gapped BLAST and PSI-BLAST: a newgeneration of protein database search programs. Nucleic Acids Res. 25:3389–3402.Anantharaman V, Aravind L, Koonin EV (2003) Emergence of diverse biochemical activitiesin evolutionarily conserved structural scaffolds of proteins Curr Opin Chem Biol7:12–20.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 29:231–262.Barker JA, Thornton JM (2003) An algorithm for constraint-based structural template matching:application to 3D templates with statistical analysis. Bioinformatics 19:1644–1649.Berrondo M, Ostermeier M, Gray JJ (2008) Structure prediction of domain insertion proteins fromstructures of individual domains. Structure 16:513–527.Bowers PM, Pellegrini M, Thompson MJ, et al. (2004) Prolinks: a database of protein functionallinkages derived from coevolution. Genome Biol 5:R35.Bryson K, McGuffin LJ, Marsden RL, et al. (2005) Protein structure prediction servers atUniversity College London. Nucleic Acids Res 33:W36–W38.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–D266.Carugo O (2006) Rapid methods for comparing protein structures and scanning structure databases.Curr. Bioinformatics 1:75–83.Cuff ME, Li H, Moy S, et al. (2007) Crystal structure of an acetyltransferase protein from Vibriocholerae strain N16961. Proteins 69:422–427.Fischer D, Eisenberg D (1997) Assigning folds to the proteins encoded by the genome ofMycoplasma genitalium. Proc. Natl Acad Sci USA 94:11929–11934.Glaser F, Pupko T, Paz I, et al. (2003) ConSurf: identification of functional regions in proteins bysurface-mapping of phylogenetic information. Bioinformatics 19:163–164.Hermann JC, Ghanem E, Li Y, et al. (2006) Predicting substrates by docking high-energy intermediatesto enzyme structures. J. Am. Chem. Soc. 128:15882–15891.Holm L, Sander C (1998) Touring the fold space with DALI/FSSP. Nucleic Acids Res.26:316–319.Hulo N, Sigrist CJ, Le Saux V, et al. (2004) Recent improvements to the PROSITE database.Nucleic Acids Res. 32:D134–D137.Hutchinson EG, Thornton JM (1990) HERA: a program to draw schematic diagrams of proteinsecondary structures. Proteins 8:203–212.Jeffery CJ (1999) Moonlighting proteins. Trends Biochem. Sci. 24:8–11.Jones S, Barker JA, Nobeli I, et al. (2003) Using structural motif templates to identify proteinswith DNA binding function. Nucleic Acids Res. 31:2811–2823.Kim SH, Shin DH, Choi IG, et al. (2003) Structure-based functional inference in structuralgenomics. J. Struct. Funct. Genomics 4:129–135.Kleywegt GJ (1999) Recognition of spatial motifs in protein structures. J. Mol. Biol.285:1887–1897.Krissinel E, Henrick K (2004) Secondary-structure matching (SSM), a new tool for fast proteinstructure alignment in three dimensions. Acta Crystallogr. D60:2256–2268.Laskowski RA (1995) SURFNET: a program for visualizing molecular surfaces, cavities andintermolecular interactions. J. Mol. Graph. 13:323–330.Laskowski RA, Luscombe NM, Swindells MB, et al. (1996) Protein clefts in molecular recognitionand function. Protein Science 5:2438–2452.Laskowski RA, Chistyakov VV, Thornton JM (2005a) PDBsum more: new summaries and analysesof the known 3D structures of proteins and nucleic acids. Nucleic Acids Res. 33:D266–D268.Laskowski RA, Watson JD, Thornton JM (2005b) ProFunc: a server for predicting protein functionfrom 3D structure. Nucleic Acids Res. 33:W89–W93.
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Daniel John RigdenEditorFrom Protei
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ContentsSection I Generating and In
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Contentsxi4.2.1 Alpha-Helical Bundl
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Contentsxiii7.4.2 Predicting Bindin
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Contentsxv12.3 Accuracy and Added V
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4 J. Lee et al.about 5.3 million pr
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6 J. Lee et al.Table 1.1 A list of
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8 J. Lee et al.2000; Sorin and Pand
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10 J. Lee et al.Although most knowl
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12 J. Lee et al.Fig. 1.3 Two exampl
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14 J. Lee et al.rugged containing m
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16 J. Lee et al.1.3.4 Mathematical
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18 J. Lee et al.potentials, each re
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20 J. Lee et al.viewpoint of struct
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22 J. Lee et al.Hsieh MJ, Luo R (20
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24 J. Lee et al.Sippl MJ (1990) Cal
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Chapter 2Fold RecognitionLawrence A
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2 Fold Recognition 29It has long be
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2 Fold Recognition 31Fig. 2.2 Graph
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2 Fold Recognition 33distribute the
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2 Fold Recognition 35Table 2.1 (a)
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2 Fold Recognition 37dependent on t
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2 Fold Recognition 39based on the r
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2 Fold Recognition 41The idea of co
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2 Fold Recognition 43query sequence
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2 Fold Recognition 452.3.4 Consensu
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2 Fold Recognition 472.4 Alignment
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2 Fold Recognition 49statistical me
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2 Fold Recognition 51methods (e.g.
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2 Fold Recognition 53Berman HM, Wes
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2 Fold Recognition 55Tress ML, Jone
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58 A. Fiserwith more than 50% seque
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60 A. FiserIn contrast to ab initio
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62 A. FiserTable 3.1 (continued)SWI
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64 A. Fiserbetween fold recognition
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66 A. FiserFig. 3.1 Comparing accur
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68 A. Fiserinto conserved core regi
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70 A. Fiseralignments are built and
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72 A. Fiserfold, such as the hyperv
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74 A. Fiserfunctions delivers impro
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76 A. Fiserfrom efforts of genome s
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78 A. FiserA rigorous statistical e
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80 A. Fiser(Clore et al. 1993). Cha
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82 A. FiserImproved and new methods
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84 A. FiserClaessens M, Van Cutsem
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86 A. FiserHavel TF, Snow ME (1991)
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88 A. FiserPetrey D, Xiang Z, Tang
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90 A. Fiservan Vlijmen HW, Karplus
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92 T. Nugent and D.T. Jones4.2 Stru
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94 T. Nugent and D.T. JonesFig. 4.2
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96 T. Nugent and D.T. JonesTable 4.
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98 T. Nugent and D.T. Jones2000), d
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100 T. Nugent and D.T. JonesTable 4
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102 T. Nugent and D.T. JonesFig. 4.
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104 T. Nugent and D.T. JonesFig. 4.
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106 T. Nugent and D.T. Jonessubdivi
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108 T. Nugent and D.T. Jonescomplex
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110 T. Nugent and D.T. JonesMartell
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Chapter 5Bioinformatics Approaches
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5 Structure and Function of Intrins
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Chapter 6Function Diversity Within
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6 Function Diversity Within Folds a
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Chapter 7Predicting Protein Functio
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7 Predicting Protein Function from
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Table 7.1 Online resources and tool
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Chapter 83D MotifsElaine C. Meng, B
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8 3D Motifs 189clustering similar s
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8 3D Motifs 191To improve the signa
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8 3D Motifs 193structures together.
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8 3D Motifs 195Table 8.1 (continued
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8 3D Motifs 1978.3.1 User-Defined M
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8 3D Motifs 199Fig. 8.3 The FFF mot
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8 3D Motifs 2018.3.2 Motif Discover
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8 3D Motifs 203In addition to SITE
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8 3D Motifs 205folds; they shared a
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8 3D Motifs 207from a training set
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8 3D Motifs 209Table 8.3 Web server
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8 3D Motifs 211its greater overall
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8 3D Motifs 213Ideally, a 3D motif
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8 3D Motifs 215Ivanisenko VA, Pintu
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Chapter 9Protein Dynamics: From Str
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Page 266 and 267: 260 R.A. LaskowskiFig. 10.4 Schemat
Page 268 and 269: 262 R.A. Laskowskiaccessibility and
Page 270 and 271: 264 R.A. LaskowskiFig. 10.6 A ligan
Page 272 and 273: 266 R.A. LaskowskiGly97Gly99Tyr98Ty
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Page 278 and 279: 272 R.A. LaskowskiXenarios I, Salwi
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Page 298 and 299: Chapter 12Prediction of Protein Fun
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Page 324 and 325: 320 IndexConsensus templates, 205Co
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322 IndexLigand-binding templates,
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324 IndexStructure-function linkage
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