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x c * " c predicted Standard c ! 1 predicted hinge 1 nonhinge 1 HAG " c ! 0.042 Average 0.062 Deviation 0.010 Description of c Dummy constant for fitting StoneHinge 1 0 0.012 0.012 0.003 StoneHinge flexible regions Raw HingeSeq score; high values more HingeSeq high low ! 0.004 0.004 0.001 likely hinge locations TLS domain boundary, for N=2..5 TLSMD 0 1 -0.029 -0.048 0.009 putative domains hNM1 low high -0.010 -0.010 0.003 First normal mode displacement Continuous Domain Boundary Identifier hNMb 1 0 0.190 0.196 0.030 most likely hinge location Secondary hinge predictions similar to but not reported by the Continuous hNMc 2,3,4.. 0 0.028 0.035 0.007 Domain Boundary Identifier. Regions excluded from continuous hNMd 1 0 -.0007 -0.0006 0.0007 domains Single-cut FlexOracle (with FoldX) energy, normalized from0 to 1.
test true c positive positive sensitivity specificity p-value StoneHinge 1204 42 0.28 0.91 2.7E-11 HingeSeq 771 13 0.09 0.94 0.11 TLSMD 455 30 0.20 0.97 4.8E-15 hNMa 1279 37 0.24 0.91 8.7E-08 hNMb 126 31 0.20 0.99 3.2E-33 hNMc 517 26 0.17 0.96 1.7E-10 hNMd 1545 49 0.32 0.89 1.1E-11 hNMe 235 35 0.23 0.99 2.0e-29 FO1 563 8 0.05 0.96 0.32 FO1M 292 14 0.09 0.98 6.6E-06 FO 272 62 0.41 0.98 9.2E-66 Table 4.3: Performance of the predictors against the Hinge Atlas Gold annotation. Test positives are predicted hinge locations. hNM1 and FO1 give continuous (rather than discrete) output, normalized to range from 0 to 1 for each protein. Therefore for hNM1 and FO1 we took values below .02 and 0.1, respectively, as test positives. For HingeSeq we took values above 0.4 as test positives. here were a total of 13259 residues in the HAG, of which 152(13107) were Gold Standard Positives(Negatives). Therefore for the example of StoneHinge, sensitivity was calculated as 42/152=0.28 and specificity was (13259-1204)/13107=0.91. For the same example, p-value was computed as the probability of finding 42 or more true positive residues in a set of 1204 residues selected randomly and without replacement from a set of 13259, using the cumulative hypergeometric distribution. 233
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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
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a. 145
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Figure 3.5: Lir-1 (closed) Morph ID
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. c. 149
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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
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 and 196: hinge, it is usually predicted by a
Page 197 and 198: Supplementary methods Statistical t
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: Tables Predictor Basis Max. hinge p
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
Page 247 and 248: coordinate. This phenomenon is know
Page 249 and 250: ! At the end of each equilibration
Page 251 and 252: aborted. This marked the correspond
Page 253 and 254: sRMSD has a major limitation that m
Page 255 and 256: with respect to the starting struct
Page 257 and 258: generated structure with respect to
Page 259 and 260: Ribose Binding Protein (RBP) As des
Page 261 and 262: strikingly similar both to the holo
Page 263 and 264: energy minimization. The minimizati
Page 265 and 266: Figures Figure 5.1: Assignment of r
Page 267 and 268: Figure 5.3: Results for glutamine b
Page 269 and 270: Figure 5.4: Results for biotin carb
Page 271 and 272: Figure 5.6: Results for Adenylate K
Page 273 and 274: close to the holo. The structure wi
Page 275 and 276: Table 5.1: MolMovDB ID, PDB ID, fre
Page 277 and 278: with sRMSD; however its main utilit
Page 279 and 280: morph server, and left confident th
Page 281 and 282: 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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