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Number of hinge points 1 76 2 75 3 56 4 6 5 1 Total: 214 Number of protein pairs (morphs) Table 2.7: Number of hinge points per protein in the Hinge Atlas 102
Total resid. in Hinge Atlas 54839 Hinges in Hinge Atlas 873 Total residues with HingeSeq score > .5 Hinge residues with HingeSeq score > .5 924 48 p-value 1.5•10 -12 Table 2.8: Statistical analysis of HingeSeq predictor. The low p-value indicates that the predictor results have high statistical significance. However the low sensitivity limits its potential predictive value. 103
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Abstract Flexibility and domain dyn
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Flexibility and domain dynamics of
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Table of Contents Table of figures
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Can hinges be predicted by a simple
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FlexOracle (FO1, FO1M, FO) 176 Defi
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Conclusions 279 References 281 Tabl
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Table of tables Table 2.1: Amino ac
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Acknowledgements Committee: Mark Ge
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Introduction The problem of predict
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Ab initio methods attempt to model
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potential for simplification, motio
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Chapter 1: The molecular motions da
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MolMovDB is a resource for studying
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voids in proteins, helix-helix pack
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A full-feature version of FIRST5 wi
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gradual transition from the initial
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energy. Thus the first residue list
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activity, DNA-directed DNA polymera
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homology table to an entry in the C
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Highlight active sites from the CSA
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Figure 1.3: Conformational change a
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particular, we found that hinges te
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and the holo. In this case it is po
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Our molecular motions database serv
Page 51 and 52: We first made a simple GOR(Garnier-
Page 53 and 54: The morph trajectory was sterically
Page 55 and 56: protein in the Jmol window to his/h
Page 57 and 58: of the hinge was otherwise unclear,
Page 59 and 60: Catalytic Sites Atlas (nonredundant
Page 61 and 62: ! ! ! ! ! h c = number of times res
Page 63 and 64: ! ! ! ! µ h " d c D # H . It is eq
Page 65 and 66: As mentioned earlier, the fact that
Page 67 and 68: STRIDE[50] recognizes secondary str
Page 69 and 70: ! ! alignment at this position[24,
Page 71 and 72: To test this idea, we decided to ca
Page 73 and 74: GOR method is useful for predicting
Page 75 and 76: ! HI active"site (i) as 0.4 for res
Page 77 and 78: lowered, and the area under the cur
Page 79 and 80: would be preferable to the other, o
Page 81 and 82: Discussion Correlations were found
Page 83 and 84: Sequence in the immediate neighborh
Page 85 and 86: Figures p-value 0.5 0.25 0 .01 PHE
Page 87 and 88: Figure 2.3: Secondary structure Res
Page 89 and 90: Figure 2.5: Conservation: full set
Page 91 and 92: Figure 2.7: Solvent accessible surf
Page 93 and 94: completely random predictor, with a
Page 95 and 96: samples 1800 1600 1400 1200 1000 80
Page 97 and 98: m = distance from nearest residues
Page 99 and 100: Hinge All Hinge Residues residues R
Page 101: in hinge residues HI p-value 1 277
Page 105 and 106: Chi- Computer annotated set Hinge A
Page 107 and 108: BMC: Bioinformatics, we present the
Page 109 and 110: hinges. Kundu et al. use the lowest
Page 111 and 112: Domains can move relative to each o
Page 113 and 114: The quantity ! E(i) represents the
Page 115 and 116: Identification of local minima As w
Page 117 and 118: compute FoldX_energy (stability of
Page 119 and 120: energy element of each cluster was
Page 121 and 122: At least two sets of atomic coordin
Page 123 and 124: ! FN (false negatives): Number of r
Page 125 and 126: We observed qualitatively (figures
Page 127 and 128: pairs of structures used to generat
Page 129 and 130: coordinate set does not significant
Page 131 and 132: The LIR family is composed of eight
Page 133 and 134: CaM is a major calcium-binding prot
Page 135 and 136: The results of running FlexOracle a
Page 137 and 138: Figure 3.2: Results for individual
Page 139 and 140: a. 139
Page 141 and 142: Figure 3.3: Folylpolyglutamate Synt
Page 143 and 144: . c. 143
Page 145 and 146: a. 145
Page 147 and 148: Figure 3.5: Lir-1 (closed) Morph ID
Page 149 and 150: . c. 149
Page 151 and 152: a. 151
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Figure 3.7: Ribose binding protein
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. c. 155
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Tables GNM 157 Single-cut predictor
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Chapter 4: HingeMaster: normal mode
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The problem of hinge prediction is
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Translation Libration Screw Motion
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! [ K] = [ U] " [ ] 2 [ U] T Where
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generated one ROC curve for each mo
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! ! 1 (l " k) A(k,l) = 2 % ' $ C(i,
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however, since we found that the Co
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A key part of this analysis involve
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describe its net vibrational displa
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! Because it cuts the backbone at t
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! ! x HingeMaster = x" # y . [6] 2
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different values of ! " * and gener
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manually select domains and color p
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E. coli resides in the periplasmic
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The results for this protein are sh
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esidues (62). As is customary we al
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FlexOracle (FO) The FlexOracle algo
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extra breakpoints based on visual i
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hinge, it is usually predicted by a
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Supplementary methods Statistical t
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! ! ! eigenvector. The resulting re
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TNC induces a conformational change
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possibility that unexpected results
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UDP-N-acetylglucosamine enolpyruvyl
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predicted both hinges, again with m
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Most predictors (including FO, Ston
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FO, hNMb, and hNMd were completely
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HingeMaster makes a strong predicti
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Figure 4.2: ROC curves for HingeMas
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Figure 4.3: HingeMaster results for
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d. e. 219
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221
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Figure 4.5: Human lactoferrin (open
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Figure 4.6: Troponin C (TNC) Morph
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Figure 4.7: Calmodulin, calcium fre
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229
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Tables Predictor Basis Max. hinge p
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test true c positive positive sensi
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235 Closed Metal bound # of hinge p
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Chapter 5: The Conformation Explore
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ending, which involves a rigid regi
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lengths and angles)[89]. The equili
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for holo as well as apo forms, but
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queried using the “?” button. O
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coordinate. This phenomenon is know
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! At the end of each equilibration
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aborted. This marked the correspond
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sRMSD has a major limitation that m
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with respect to the starting struct
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generated structure with respect to
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Ribose Binding Protein (RBP) As des
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strikingly similar both to the holo
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energy minimization. The minimizati
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Figures Figure 5.1: Assignment of r
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Figure 5.3: Results for glutamine b
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Figure 5.4: Results for biotin carb
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Figure 5.6: Results for Adenylate K
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close to the holo. The structure wi
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Table 5.1: MolMovDB ID, PDB ID, fre
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with sRMSD; however its main utilit
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morph server, and left confident th
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9. M Gerstein RJ, T Johnson, J Tsai
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28. Wriggers W, Schulten K: Protein
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45. Dumontier M, Yao R, Feldman HJ,
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62. Thorpe MF, D.J. Jacobs, M.V. Ch
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81. Winn MD, Isupov MN, Murshudov G
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98. Morris GM, Goodsell DS, Hallida
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115. Miyazawa T: Normal Vibrations
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