Computational Methods for Protein Structure Prediction & Modeling V1 - Xu Xu and Liang
.pdf390 |
Index |
contact map prediction 255, 262
contact order (CO) |
258–259, 269 |
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contact potentials |
74, 109, 256 |
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contact substitution matrix |
271 |
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contact, residues 73 |
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contiguous, domain |
129, 134 |
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convex hull 95, 185, 191–192 |
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cooperative, cooperativity |
110, 231 |
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correlated mutation |
262–263, 265–268, |
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271–272 |
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Coulombic interactions 45, 47 convex spherical surface 184
Critical Assessment of Structure Prediction (CASP)
12, 14–16, 25, 238–239, 268–269, 337, 347 cross-linking 288–289, 329
crossstructure 293, 295–296
cryo-EM 27–28, 181–182, 285, 292, 359, 363–365, 370–371, 374, 377, 382
curved lineg segments 184 CVFF 58
Dali 22, 151, 154–156, 161, 164–165, 167,
169, 171
deconvolution method |
366–367, 370–371, 373 |
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Decoys ‘R’Us |
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101 |
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DEE (Dead End Elimination) |
13 |
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Delaunay complex |
186–187 |
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Delaunay edge |
89, 185–186, 192 |
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Delaunay tetrahedrization |
112, 185–187, |
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191–193, 196, 202 |
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Delaunay triangulation |
88, 110, 185, 190, |
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192–193 |
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density maps |
27–28, 225, 359 |
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DFIRE |
87, 111–112 |
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dihedral angle |
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47, 52, 55, 73–74, 329, 377–378 |
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discontinuous molecular dynamics 303 |
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discrete flow |
190–191 |
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discrete molecular dynamics |
303 |
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DisEMBL 226, 238 |
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DISOPRED |
226, 239 |
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disordered region detection |
224, 243 |
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DISPRO |
226, 239 |
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distance matrix |
149, 153, 175, 256–257 |
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distance matrix error (DME) |
150, 256 |
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docking 12–13, 15, 24–26 |
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domain assignment |
22–23 |
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domain, structural |
129–130 |
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domain-domain interactions |
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22, 24 |
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DomainParser 22, 133, 137, 139, 141–142 |
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double dynamic programming |
8, 152–153 |
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Drude oscillator |
59 |
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drug design |
59, 323 |
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dynamic programming 7–8, 152–153, 155–156,
159, 197, 219, 236, 324, 335
edge-flip |
192 |
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effective energy |
71, 110, 336–337 |
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effective resolution |
373, 384 |
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elastic scoring measure |
154 |
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electro density map |
181, 225, 365 |
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electron cryomicroscopy |
27, 359 |
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electron microscopy |
27, 181, 271, 285, 291, 323 |
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electron spin resonance |
286 |
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electronegativity equilization methods 52 |
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electronic polarizability |
52, 59 |
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electrostatic interactions |
2, 26, 46, 49, 53, 82, |
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334 |
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electrostatic potential |
82 |
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elementary surface pieces |
184 |
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elongation kinetics |
290 |
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EM density map |
27–28, 31, 364, 374 |
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empirical force field optimization 51 |
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empirical Force Fields |
45 |
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empirical potential function |
360, 373–374 |
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ENCAD 50, 58, 344–345 |
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energy minimization |
2–5, 11, 339, 341, 344 |
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ensemble |
30, 49, 97, 101, 106, 111, 171–173, |
239, 271
ensemble averaging 360, 374 ensemble classifier 171–173 environmental features 7
EPR 291, 295 ESP 52–53
Euclidean distance 77, 114, 175, 185, 214 |
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evolutionary relationship |
151, 187, 166–167, |
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196, 319 |
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Ewald method |
49 |
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extended atom force field |
58 |
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F3C |
49–50 |
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family 4, 12, 21, 166, 168 |
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feature vector |
162–163, 175 |
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FFAS |
8 |
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FFT (Fast Fourier Transform) |
25–26 |
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fold 2, 5–9, 11, 23 |
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fold recognition |
6, 23, 29 |
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FoldIndex |
226, 238 |
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force field |
2, 45 |
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forward/backward algorithm |
268 |
Fourier transform infrared spectroscopy 286 fragment 3, 8, 11, 24, 129, 133–135 framework 5, 71–72, 158, 328, 336, 344 FSSP 161, 167, 176
function annotation 323
Index |
391 |
function prediction |
181, 195–197 |
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functional interpretation |
359 |
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fused ball model |
182 |
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gaps 97, 148, 150, 155, 219, 227, 229, 235, |
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321, 323, 325–327, 344–345 |
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generalized-Born 50, 332, 336 |
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genetic algorithm |
11, 25–26, 267, 335, 344 |
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genomes 16, 19, 29, 31, 166, 226 |
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GenTHREADER |
8 |
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geometric hashing |
26, 149, 152, 155–156, 158, |
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160, 196 |
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geometric nature of discrimination |
95 |
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geometric potential function |
88, 101, 105, 112, |
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200 |
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geometry-based procedure |
46, 181 |
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global free-energy minimum |
9, 320 |
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global optimality |
326 |
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GLOBPLOT |
226, 239 |
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Go models |
299 |
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GROMOS 2, 46, 50, 58 |
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hard-sphere model |
182 |
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Helixhunter 28, 359, 363, 373 |
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Hidden Markov models (HMM) |
8, 19, 210, 213, |
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216, 223, 234, 262, 325 |
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HMMSTR |
268 |
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homologous modeling |
3–4 |
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homologous topology 167
homology detection 6, 8–9, 29, 213, 229,
324–325
homology modeling 3–6, 9, 12–13, 18, 22–23,
25, 28, 31, 230–231, 319–322
homotopy equivalent |
184 |
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HP model |
10, 84, 109, 298–299 |
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hydrogen bonds |
2, 47, 208, 266, 285, 296, 326, |
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334, 342, 344 |
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hydrogen-deuterium exchange |
287 |
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hydrophobic core |
23, 126, 130–131, 221, 303 |
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idealized ball model |
182 |
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Implicit solvation models |
50 |
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Improper angle |
46–47, 52 |
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inclusion bodies |
281, 300 |
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inclusion-exclusion formula |
188, 190 |
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index structure 161–163, 174–175 |
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insertion 4–5, 192, 227, 231, 289–290, |
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321–323, 325–326, 330, 337–342 |
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InsightII |
4, 327 |
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interatomic interactions |
1–7 |
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inter-domain, contact |
127 |
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interface, domain 130, 138–139, 141 intermediate resolution 27, 292, 301, 359–360 inter-residue contact 274
inverse spherical surface 184
iterative dynamic programming 153, 156, 159
Jpred 235–236
kernel voxel 360 kinetic partitioning 281
k-nearest neighbour (kNN) 210, 214, 232–233 knowledge-based effective potential function 72
knowledge-based potential |
71–73, 75–76, |
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85–86, 93–94, 101–103, 108–115 |
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K-segment clustering |
366, 368 |
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Langevin Dipoles Model |
51 |
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lattice models |
10, 230, 297–299, 301 |
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Lee-Richards surface |
183 |
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Lennard-Jones (LJ) |
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46–47, 134, 302 |
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Levinthal’s Paradox |
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2, 280 |
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ligand binding |
231, 291, 323, 345 |
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likelihood matrix |
264 |
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limited proteolysis |
287–288, 291, 297 |
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local conservation |
197 |
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local contacts |
257–259, 264–265 |
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local peak filter |
366, 368 |
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local structure motifs |
268 |
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locally Delaunay 192–193 |
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locally enhanced sampling |
49 |
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loop connectivity |
359, 373 |
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loop prediction |
331–334, 338 |
loops 5, 12, 19, 134–135, 230, 259, 322–323, 327, 330–332, 336, 345, 373–374, 377
machine learning 19–20, 100, 171, 210–211,
213, 215, 217, 222, 232, 239, 255, 257, 272–273
maximum disk inclusion number 360
MD (Molecular Dynamics simulation) 11, 13, 56,
59, 302, 336
MD simulation 9, 11, 20–21, 48–52, 54–56, 291–296, 301, 303, 336
median of energy value 380 membrane proteome 21–22 meta servers 8, 16, 343–344
methods, for domain partitioning 125, 129 minimum local thickness 360
misfolded models 337
Miyazawa-Jernigan contact statistical potential 71 MM3 66
MMFF 48, 58
392 |
Index |
ModBase 29 |
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model assessment |
336–337 |
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model building |
289, 322, 325, 327–329, 333, |
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337–339, 343 |
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model quality |
13, 335–336, 344 |
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modeling target |
3, 347–348 |
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Modeller 5, 13, 24, 28–29, 327, 329, 344–345 |
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molcular surface (MS) |
184, 287, 329 |
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molecular dynamics |
2, 9, 20, 48, 303 |
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molecular dynamics simulations |
9, 11, 20–21, |
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48–52, 54–56, 291–296, 301, 303, 336 |
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molecular mechanics |
2, 45, 332 |
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Monte Carlo simulation (MC) |
223–224 |
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Morphological analysis |
360, 366 |
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Morse function |
47 |
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Motif 11, 20, 147, 149–150, 157–159, 166,
173, 175–176, 196–197, 221–222, 305, 320
Multi-dimensional hyperplane |
95, 100 |
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multi-domain, chains |
142 |
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multiple sequence alignment |
23, 207, 210, 212, |
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228, 230, 262 |
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multiple structure alignment |
147, 149, 157, |
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159–161, 175–176, 325, 327 |
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multiple-domain proteins |
22 |
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native conformation |
1–2, 72, 94, 101, 106, 108, |
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200, 331–334, 336, 341 |
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Native topology |
359–360, 373–375, 377, |
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379–384 |
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neural network (NN) |
19–20, 168, 171, |
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215–216, 222 |
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nonadditivity effect |
110 |
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non-contiguous, domain |
129, 132, 134–135 |
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Non-local contacts |
264, 266, 269–270, 272 |
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non-order-preserving 150 |
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Non-sequential structure alignment |
150 |
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nucleated growth polymerization |
289 |
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nucleation 270, 282, 290, 303 |
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nucleation site |
270 |
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OPLS 45, 50, 53–55 |
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OPLS/AA |
45, 54–56 |
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OPLS/UA |
58 |
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optimal local alignment |
324 |
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optimized linear potential function |
97–98, 115 |
optimized nonlinear potential function 98, 100,
106
order preserving 150 orthogonal bundle 377
packing 13, 90–91, 101, 104, 112, 130 packing geometry 377
pair-wise search |
325 |
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parallel tempering |
49, 181 |
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PARAM19 |
181 |
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parameter optimization |
51, 56 |
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parametrization |
65 |
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partial atomic charges |
|
47, 52–55, 58 |
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particle Mesh Ewald |
49 |
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partition function |
74–75, 106–108, 110–111 |
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partitioning 125–129, 133, 137–138, 142 |
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pathway models |
268 |
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PDB 28, 56, 142 |
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PDISORDER |
226, 239 |
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PDP 22, 134, 139, 141 |
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phase diagram |
300, 303 |
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PHD 212, 230, 232–233, 235–236 |
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phi, psi angles |
52 |
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photo-affinity labeling |
|
289 |
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physical potential function |
114 |
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physical/non-physical contacts |
299 |
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physical-chemical energy |
341 |
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physics-based effective potential function 72 |
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pockets |
190–191, 194–195 |
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Poisson-Boltzmann 50, 332 |
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polyalanine |
302–303 |
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polyglutamine 282, 289–290, 295 |
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PONDR |
226, 238 |
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position specific score matrix |
325 |
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potential energy functions |
45, 48 |
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potential function |
9, 71–76, 85–86, 88, 93–95, |
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97–99 |
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power distance |
185 |
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PRALINE |
229 |
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profile analysis |
324, 346 |
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profile-based 6, 8 |
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profile-profile alignment |
6, 8–9 |
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PROFsec 229, 233, 235–236 |
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protein classification |
165, 168, 174 |
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protein complexes |
3, 15, 25 |
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protein design |
71–72, 94, 99, 105–106 |
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protein family |
4 |
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protein fold |
7, 11, 105 |
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Protein folding |
9–10, 50, 59, 71–72, 84, 94, 99, |
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101 |
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protein folding simulation |
9 |
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Protein force fields |
54–58 |
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protein function |
195–200 |
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protein interaction pathways |
323 |
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protein structure alignment |
147, 174 |
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protein surface evolution |
197 |
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protein threading |
7, 102, 148, 291, 293–294 |
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protein-protein docking |
13, 15, 26, 72, 103, |
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200 |
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Index |
393 |
protofilament 280, 283–286, 292, 294,
296–298, 302, 305
Pseudo-atomic model 359
PSI (Protein Structure Index) |
161–162, 165 |
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PSI-blast 8, 168–171, 212 |
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PSIPred |
212, 233 |
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PSSM (Position Specific Scoring Matrix) |
7–8, |
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212, 233–235, 325 |
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PUU 23, 139, 141–142 |
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QM 45, 48, 51–56 |
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quantum mechanical |
45, 71 |
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quasi-chemical approximation |
80 |
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RADAR |
227, 240–241 |
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reduced models |
|
10 |
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re-entrant surface |
184, 187 |
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reference frame |
|
155–156, 158, 257 |
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reference state |
72, 75–76, 80 |
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refolding |
1, 281–282 |
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remote homolog |
|
212, 319 |
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remote homology recognition |
6 |
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REP 241 |
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repeats detection |
|
226–227, 232, 241, 243 |
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replica-exchange |
|
49 |
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REPRO |
|
227, 240 |
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Resolution dependency 363 |
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RESP |
53–55, 58 |
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reverse Boltzmann Principle |
7 |
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rigid-body assembly |
321 |
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Root mean square deviation (RMSD) |
257 |
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Root Mean Square Distance |
150, 175, 195, 197, |
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327, |
343 |
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ROSETTA 9, 11, 12, 15, 29, 103, 107, 336 |
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Rule-based filtering |
269 |
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salt bridges 221, 266, 326 |
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SAM 8, 168, 234–235, 325 |
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scanning proline mutagenesis |
284 |
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SCOP 22, 23, 126, 137,139, 158, 164, |
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166–169 |
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scoring matrix |
8, 151, 153, 197, 212, 335, 337 |
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SCR (structurally conserved region) |
5 |
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secondary structure prediction |
18–19, 207–220, |
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222, |
224 |
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segment assembling |
11 |
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Segment clustering |
366 |
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segment matching |
327–329 |
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Self-organizing map algorithm (SOM) |
267 |
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semi-empirical effective potential function |
72 |
|||||||
Sensitivity 6, 8–9, 19–20, 24, 176, 198, 211, |
||||||||
237, |
243 |
|
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|
sequence alignment 4–8, 23 sequence analysis 196
Sequence conservation 23–24, 262, 265, 267,
296
Sequence dependency of partition function 110
Sequence profile |
6, 8, 12, 262, 265–268, 325, |
|||
346 |
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|
sequence similarity |
6, 166, 197, 221, 227, 229, |
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294, 320 |
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sequence-structure alignment 8,24, 29, 295 |
||||
Sheetminer |
360–365 |
|
||
Sheettracer 359, 366–373, 383 |
||||
side-chain prediction |
13, 333–334 |
|||
side-chains 73, 230 |
|
|||
simplices 90, 186–189, 191, 195 |
||||
simplicial complex |
186–187, 189 |
|||
sink 137, 190–191 |
|
|||
size, domain |
24, 133–134, 138 |
|||
size, interface |
103 |
|
|
|
Skeleton of Secondary Structure |
373 |
|||
solid state NMR |
284, 286, 291, 293, 295, 304 |
|||
solvent accessibility |
7, 50, 74, 90, 239, 266, |
|||
286, 325, 334 |
|
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|
|
solvent accessible surface (SA) |
73, 183–184, |
|||
188, 195, 200, 332, 342 |
|
|||
solvent ball |
183–184, 191 |
|
||
space filling model |
182 |
|
||
spatial restraints |
5, 13, 329 |
|
SPC 49–50, 52, 55
SPC/E 49–50
specificity 13–14, 19, 198, 224, 322, 362–363, 367, 369–370, 372
sphere intersection graph (SIG) 261–262
SSAP 152–153, 167 SSPro 229, 233–234, 236 star alignment 159 statistical energy 92, 111
statistical potential 7, 23, 71, 74, 76, 85, 88, 90,
94, 105–109, 113, 115
statistical potential function 74, 76, 85,
107–108, 113
structure determination 30, 359, 384 structural differences 13–14, 284, 303
structural genomics 9, 16–17, 29–30, 125–126,
200, 319, 321–323
structural motif 147, 149, 157–158, 175, 221,
272
structure alignment 8, 24, 29, 147, 149–150,
152, 157, 159–161, 167, 174 structure prediction software 232 structure refinement 110, 114, 373 structure template 7, 24
394 |
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Index |
structure-sequence conservation |
23, 262, 265, |
tracing secondary structure |
||||||||||||
296 |
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TRILOGY |
158 |
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substitution matrices |
324 |
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triplet |
110, 162–163 |
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substrate specificities |
323 |
|
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TRUST |
227, 243 |
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superfamily 164, 166, 168–173, 239 |
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|||||||
super-secondary structure prediction |
236, 243 |
unfolding-induced aggregation 280–281 |
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support vector machines (SVMs) |
20, 210, 217, |
union of balls |
182–183, 188, 202 |
|||||||||||
222–223, 235 |
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|
united atom |
54, 58, 182, 301–302 |
|||||||
supramolecular complex |
27 |
|
|
united atom force field |
58 |
|||||||||
SVR (structurally conserved region) |
4–5 |
up-down bundle |
377 |
|
||||||||||
SWISS-MODEL 5, 344–345 |
|
|
Urey-Bradley |
46–47, 51–52 |
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SymSSP 236 |
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van der Waals radii |
133, 182, 342 |
|||||
Template 3–9, 12–13, 22, 24, 27–28, 196, 198, |
variable regions |
4, 209, 321–322, 326–327, |
||||||||||||
230, 255–256, 268, 272, 294–295, 320–340, |
330, 336, 344 |
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343–346 |
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Vast 23, 156, 161, 164–165, 169–171 |
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template consensus sequences 324 |
|
vibrational spectra |
48, 52, 55 |
|||||||||||
tertiary structure prediction |
9, 207, 230 |
voids 87, 190–191, 193–197 |
||||||||||||
TESS |
158 |
|
|
|
|
|
|
volume exclusion |
|
109 |
|
|||
thermodynamic analysis |
290 |
|
|
Voronoi cell |
133, 184–187 |
|||||||||
thermodynamic control of folding |
280 |
Voronoi diagram |
|
88, 184–186, 191, |
||||||||||
thermodynamic hypothesis |
71, 94, 115 |
193–194 |
|
|
|
|
||||||||
threading 6–9, 12, 22, 24, 27–29, 102, 106, |
Voronoi edge |
89, 186–187 |
||||||||||||
148, 222, 224, 256, 291, 293–296, 384 |
Voronoi plane |
186, 188 |
||||||||||||
Tinker |
60 |
|
|
|
|
|
|
|
|
|
|
|
|
|
TIP3P 49, 52, 55 |
|
|
|
|
|
WD-repeats |
273 |
|
|
|||||
TIP4P 49–50, 52, 55 |
|
|
|
|
|
|
|
|
|
|
|
|||
topological structure |
186, 190, 200–201 |
X-ray crystallography |
17, 181, 319, 323, 359 |
|||||||||||
topology 18, 21, 167, 186, 201, 210, 231, 260, |
X-ray diffraction |
|
20, 22, 181–182, 279, 284, |
|||||||||||
359–360, 373–375, 377–383 |
|
|
292, |
365 |
|
|
|
|
||||||
topology model |
18, 20–21 |
|
|
|
X-ray fiber diffraction |
289 |
||||||||
TOPS diagram |
260 |
|
|
|
|
|
|
|
|
|
|
|
|
|
torsion angle 5, 46–47, 333–334, 337, 341 |
YASPIN |
216, 234 |
|
(continued from page ii)
Physics of the Human Body: A Physical View of Physiology Herman, I.P., 2006
Intermediate Physics for Medicine and Biology Hobbie, R.K., Roth, B., 2006
Computational Methods for Protein Structure Prediction and Modeling (2 volume set) Xu, Y., Xu, D., Liang, J. (Eds.) 2006
Artificial Sight: Basic Research, Biomedical Engineering, and Clinical Advances, Humayun, Weiland, Greenbaum., 2006
Physics and Energy Landscapes of Proteins Fraunfelder, H., Austin, R., Chan. S., 2006
Biological Membrane Ion Channels Chung, S.H., Anderson, O.S., Krishnamurthy, V.V., 2006
Cell Motility, Lenz, P., 2007
Applications of Physics in Radiation Oncology, Goitein, M., 2007
Statistical Physics of Macromolecules, Khokhlov, A., Grosberg, A.Y., Pande, V.S. 2007
Biological Physics, Benedek, G., Villars, F., 2007
Protein Structure Protein Modeling, Kurochikina, N., 2007
Three-Dimensional Shape Perception, Zaidi, Q., 2007
Structural Approaches to Sequence Evolution, Bastolla, U.
Radiobiologically Optimized Radiation Therapy, Brahme, A.
Biological Optical Microscopy, Cheng, P.
Microscopic Imaging, Gu, M.
Deciphering Complex Signatures: Applications in Life Sciences, Morfill, G.
Biomedical Opto-Acoustics, Oraevsky, A.A.
Mathematical Methods in Biology: Mathematics for Ecology and Environmental Sciences,
Takeuchi, Y.
Mathematical Methods in Biology: Mathematics for Life Science and Medicine, Takeuchi, Y.
In Vivo Optical Biopsy of the Human Retina, Drexler, W., Fujimoto, J.
Tissue Engineering: Scaffold Material, Design and Fabrication Principles, Hutmacher, D.W.
Ion Beam Therapy, Kraft, G.H.
Biomaterials Engineering: Implants, Materials and Tissues, Helsen, J.A.