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is reasonably successful in these cases. TLSMD is comparatively weak at distinguishing domain from non-domain motion, but can find smaller scale motions not detected by FO and hNMb, and its accuracy is unaffected by bound metals. Stonehinge lacks precision but is good at finding the general region of the hinge. Altogether, only a few hinges escaped detection by one or another of the methods. We found that FO1, FO1M, HingeSeq, hNMa, and hNMd were of very little value compared to the others. The combination of highly specific predictors which usually did well but were sometimes somewhat off the mark, with predictors which identified broad swathes where the hinges were likely to be, resulted in a predictor which assigned a hinge score to each residue rather than a binary prediction. The output of HingeMaster strongly indicates the pinpointed location of the hinge predicted by FOC and hNMb, but less dramatically points out alternative locations. When interpreted by a critical eye, these results could bring insight even when one or more of the predictors is incorrect. Some of this is visible in the results for individual proteins as discussed. Conclusions We demonstrated the strengths and weaknesses of several predictors, including a set of normal mode based tools. We show that for 29 of the 40 proteins in HAG at least one predictor is completely successful under the loose criterion. For 10 of the remaining 11, at least one predictor was partly successful. HingeMaster weighs the correlation of each predictor to the HAG hinge annotations and presents the combined results in a visually understandable way. This combined predictor is shown to robustly produce ROC curves demonstrating high predictive power. 196
Supplementary methods Statistical terms We use several statistical terms which are standard but which we clarify for use in the current context: Test positives: Residues with Test negatives: Residues with HS(i)greater than or equal to a certain threshold. HS(i)less than a certain threshold. Gold standard positives: ! Residues annotated as hinges in the Hinge Atlas. Gold standard negatives: ! Residues which are not in hinges according to the Hinge Atlas annotation. True positives (TP): Those residues that are both test positives and gold standard positives. True negatives (TN): Residues that are both test negatives and gold standard negatives. False positives (FP): Residues that are test positives and gold standard negatives. False negatives (FN): Residues that are test negatives and gold standard positives. ROC curve 197
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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
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We first made a simple GOR(Garnier-
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The morph trajectory was sterically
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protein in the Jmol window to his/h
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of the hinge was otherwise unclear,
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Catalytic Sites Atlas (nonredundant
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! ! ! ! ! h c = number of times res
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! ! ! ! µ h " d c D # H . It is eq
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As mentioned earlier, the fact that
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STRIDE[50] recognizes secondary str
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! ! alignment at this position[24,
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To test this idea, we decided to ca
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GOR method is useful for predicting
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! HI active"site (i) as 0.4 for res
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lowered, and the area under the cur
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would be preferable to the other, o
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Discussion Correlations were found
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Sequence in the immediate neighborh
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Figures p-value 0.5 0.25 0 .01 PHE
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Figure 2.3: Secondary structure Res
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Figure 2.5: Conservation: full set
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Figure 2.7: Solvent accessible surf
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completely random predictor, with a
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samples 1800 1600 1400 1200 1000 80
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m = distance from nearest residues
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Hinge All Hinge Residues residues R
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in hinge residues HI p-value 1 277
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Total resid. in Hinge Atlas 54839 H
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Chi- Computer annotated set Hinge A
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BMC: Bioinformatics, we present the
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hinges. Kundu et al. use the lowest
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Domains can move relative to each o
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The quantity ! E(i) represents the
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Identification of local minima As w
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compute FoldX_energy (stability of
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energy element of each cluster was
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At least two sets of atomic coordin
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! FN (false negatives): Number of r
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We observed qualitatively (figures
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pairs of structures used to generat
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coordinate set does not significant
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The LIR family is composed of eight
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CaM is a major calcium-binding prot
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The results of running FlexOracle a
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Figure 3.2: Results for individual
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a. 139
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Figure 3.3: Folylpolyglutamate Synt
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. 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
Page 153 and 154: Figure 3.7: Ribose binding protein
Page 155 and 156: . c. 155
Page 157 and 158: Tables GNM 157 Single-cut predictor
Page 159 and 160: Chapter 4: HingeMaster: normal mode
Page 161 and 162: The problem of hinge prediction is
Page 163 and 164: Translation Libration Screw Motion
Page 165 and 166: ! [ K] = [ U] " [ ] 2 [ U] T Where
Page 167 and 168: generated one ROC curve for each mo
Page 169 and 170: ! ! 1 (l " k) A(k,l) = 2 % ' $ C(i,
Page 171 and 172: however, since we found that the Co
Page 173 and 174: A key part of this analysis involve
Page 175 and 176: describe its net vibrational displa
Page 177 and 178: ! Because it cuts the backbone at t
Page 179 and 180: ! ! x HingeMaster = x" # y . [6] 2
Page 181 and 182: different values of ! " * and gener
Page 183 and 184: manually select domains and color p
Page 185 and 186: E. coli resides in the periplasmic
Page 187 and 188: The results for this protein are sh
Page 189 and 190: esidues (62). As is customary we al
Page 191 and 192: FlexOracle (FO) The FlexOracle algo
Page 193 and 194: extra breakpoints based on visual i
Page 195: hinge, it is usually predicted by a
Page 199 and 200: ! ! ! eigenvector. The resulting re
Page 201 and 202: TNC induces a conformational change
Page 203 and 204: possibility that unexpected results
Page 205 and 206: UDP-N-acetylglucosamine enolpyruvyl
Page 207 and 208: predicted both hinges, again with m
Page 209 and 210: Most predictors (including FO, Ston
Page 211 and 212: FO, hNMb, and hNMd were completely
Page 213 and 214: HingeMaster makes a strong predicti
Page 215 and 216: Figure 4.2: ROC curves for HingeMas
Page 217 and 218: Figure 4.3: HingeMaster results for
Page 219 and 220: d. e. 219
Page 221 and 222: 221
Page 223 and 224: Figure 4.5: Human lactoferrin (open
Page 225 and 226: Figure 4.6: Troponin C (TNC) Morph
Page 227 and 228: Figure 4.7: Calmodulin, calcium fre
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Page 231 and 232: Tables Predictor Basis Max. hinge p
Page 233 and 234: test true c positive positive sensi
Page 235 and 236: 235 Closed Metal bound # of hinge p
Page 237 and 238: Chapter 5: The Conformation Explore
Page 239 and 240: ending, which involves a rigid regi
Page 241 and 242: lengths and angles)[89]. The equili
Page 243 and 244: for holo as well as apo forms, but
Page 245 and 246: 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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