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Chapter 2: Hinge Atlas: relating protein sequence to sites of structural flexibility Overview In this chapter, published in BioMedCentral: Bioinformatics, we begin investigating structural flexility, with a study of the relationship between sequence features and hinges between structural domains. Some of the tools presented in Chapter 1, especially the new interactive Morph page and the GO classifications, will be used to aid the work. The concept of structural flexibility is important for identifying domain boundaries, understanding structure-function relationships, and designing flexibility into proteins. Efforts in this field have been hampered by the lack of a proper dataset for studying characteristics of hinges. Using the Molecular Motions Database we have created a Hinge Atlas of manually annotated hinges and a statistical formalism for calculating the enrichment of various types of residues in these hinges. We found various correlations between hinges and sequence features. Some of these are expected; for instance, we found that hinges tend to occur on the surface and in coils and turns and to be enriched with small and hydrophilic residues. Others are less obvious and intuitive. In 44
particular, we found that hinges tend to coincide with active sites, but unlike the latter they are not at all conserved in evolution. We evaluate the potential for hinge prediction based on sequence. Motions play an important role in catalysis and protein-ligand interactions. Hinge bending motions comprise the largest class of known motions. Therefore it is important to relate the hinge location to sequence features, namely residue type, flanking sequence, physicochemical class, secondary structure, solvent exposure, evolutionary conservation, and proximity to active sites. To do this, we first generated the Hinge Atlas, a set of protein motions with the hinge locations manually annotated, and then studied the coincidence of these features with the hinge location. We found that all of the features have bearing on the hinge location. Most interestingly, we found that hinges tend to occur at or near active sites and yet unlike the latter are not conserved. Less surprisingly, we found that hinge residues tend to be small, not hydrophobic or aliphatic, and occur in turns and random coils on the surface. A functional sequence based hinge predictor was made which uses some of the data generated in this study. The Hinge Atlas is made available to the community for further flexibility studies. In Chapters 3 and 4 we will follow up our sequence based study of flexibility with structure based studies. In Chapter 4 we will compare sequence based and structure based methods. 45
Page 1 and 2: Abstract Flexibility and domain dyn
Page 3 and 4: Flexibility and domain dynamics of
Page 5 and 6: Table of Contents Table of figures
Page 7 and 8: Can hinges be predicted by a simple
Page 9 and 10: FlexOracle (FO1, FO1M, FO) 176 Defi
Page 11 and 12: Conclusions 279 References 281 Tabl
Page 13 and 14: Table of tables Table 2.1: Amino ac
Page 15 and 16: Acknowledgements Committee: Mark Ge
Page 17 and 18: Introduction The problem of predict
Page 19 and 20: Ab initio methods attempt to model
Page 21 and 22: potential for simplification, motio
Page 23 and 24: Chapter 1: The molecular motions da
Page 25 and 26: MolMovDB is a resource for studying
Page 27 and 28: voids in proteins, helix-helix pack
Page 29 and 30: A full-feature version of FIRST5 wi
Page 31 and 32: gradual transition from the initial
Page 33 and 34: energy. Thus the first residue list
Page 35 and 36: activity, DNA-directed DNA polymera
Page 37 and 38: homology table to an entry in the C
Page 39 and 40: Highlight active sites from the CSA
Page 43: Figure 1.3: Conformational change a
Page 47 and 48: and the holo. In this case it is po
Page 49 and 50: 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 and 102:
in hinge residues HI p-value 1 277
Page 103 and 104:
Total resid. in Hinge Atlas 54839 H
Page 105 and 106:
Chi- Computer annotated set Hinge A
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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
Page 153 and 154:
Figure 3.7: Ribose binding protein
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. c. 155
Page 157 and 158:
Tables GNM 157 Single-cut predictor
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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
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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
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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
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
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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
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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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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
Page 241 and 242:
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
Page 265 and 266:
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
Page 285 and 286:
45. Dumontier M, Yao R, Feldman HJ,
Page 287 and 288:
62. Thorpe MF, D.J. Jacobs, M.V. Ch
Page 289 and 290:
81. Winn MD, Isupov MN, Murshudov G
Page 291 and 292:
98. Morris GM, Goodsell DS, Hallida
Page 293 and 294:
115. Miyazawa T: Normal Vibrations
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