Knowledge (XXG)

Adaptive sampling

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A -> B -> C, researchers can calculate the length of the transition time between A and C by simulating the A -> B transition and the B -> C transition. The protein may fold through alternative routes which may overlap in part with the A -> B -> C pathway. Decomposing the problem in
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minima. Consequently, a straightforward simulation of this process would spend a great deal of computation to this state, with the transitions between the states – the aspects of protein folding of greater scientific interest – taking place only rarely. Adaptive sampling exploits this property to
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David E. Shaw; Martin M. Deneroff; Ron O. Dror; Jeffrey S. Kuskin; Richard H. Larson; John K. Salmon; Cliff Young; Brannon Batson; Kevin J. Bowers; Jack C. Chao; Michael P. Eastwood; Joseph Gagliardo; J. P. Grossman; C. Richard Ho; Douglas J. Ierardi, Ist (2008).
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Ron O. Dror; Robert M. Dirks; J.P. Grossman; Huafeng Xu; David E. Shaw (2012). "Biomolecular Simulation: A Computational Microscope for Molecular Biology".
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in between these states. Using adaptive sampling, molecular simulations that previously would have taken decades can be performed in a matter of weeks.
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While adaptive sampling is useful for short simulations, longer trajectories may be more helpful for certain types of biochemical problems.
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TJ Lane; Gregory Bowman; Robert McGibbon; Christian Schwantes; Vijay Pande; Bruce Borden (September 10, 2012).
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Robert B Best (2012). "Atomistic molecular simulations of protein folding".
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this manner is efficient because each step can be simulated in parallel.
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Proteins spend a large portion – nearly 96% in some cases – of their
258:"Anton, A Special-Purpose Machine for Molecular Dynamics Simulation" 201: 199: 197: 73:distributed computing project in combination with 27:when coupled with molecular dynamics simulations. 161: 159: 8: 208:"Taming the complexity of protein folding" 273: 231: 206:G. Bowman; V. Volez; V. S. Pande (2011). 120: 305:10.1146/annurev-biophys-042910-155245 212:Current Opinion in Structural Biology 130:Current Opinion in Structural Biology 19:is a technique used in computational 7: 347:Mathematical and theoretical biology 14: 69:Adaptive sampling is used by the 56:If a protein folds through the 1: 168:"Folding@home Simulation FAQ" 292:Annual Review of Biophysics 378: 39:time "waiting" in various 262:Communications of the ACM 224:10.1016/j.sbi.2010.10.006 142:10.1016/j.sbi.2011.12.001 41:thermodynamic free energy 23:to efficiently simulate 357:Computational chemistry 275:10.1145/1364782.1364802 44:simulate the protein's 342:Computational biology 105:Computational biology 362:Hidden Markov models 337:Simulation software 332:Molecular modelling 176:Stanford University 100:Hidden Markov model 75:Markov state models 110:Molecular biology 58:metastable states 21:molecular biology 17:Adaptive sampling 369: 317: 316: 286: 280: 279: 277: 252: 246: 245: 235: 203: 192: 191: 189: 187: 178:. Archived from 163: 154: 153: 125: 377: 376: 372: 371: 370: 368: 367: 366: 322: 321: 320: 288: 287: 283: 254: 253: 249: 205: 204: 195: 185: 183: 165: 164: 157: 127: 126: 122: 118: 91: 83: 67: 54: 33: 25:protein folding 12: 11: 5: 375: 373: 365: 364: 359: 354: 352:Bioinformatics 349: 344: 339: 334: 324: 323: 319: 318: 281: 247: 193: 155: 119: 117: 114: 113: 112: 107: 102: 97: 90: 87: 82: 79: 66: 63: 53: 50: 32: 29: 13: 10: 9: 6: 4: 3: 2: 374: 363: 360: 358: 355: 353: 350: 348: 345: 343: 340: 338: 335: 333: 330: 329: 327: 314: 310: 306: 302: 298: 294: 293: 285: 282: 276: 271: 267: 263: 259: 251: 248: 243: 239: 234: 229: 225: 221: 217: 213: 209: 202: 200: 198: 194: 186:September 10, 182:on 2012-09-13 181: 177: 173: 169: 162: 160: 156: 151: 147: 143: 139: 135: 131: 124: 121: 115: 111: 108: 106: 103: 101: 98: 96: 93: 92: 88: 86: 81:Disadvantages 80: 78: 76: 72: 64: 62: 59: 51: 49: 47: 42: 38: 30: 28: 26: 22: 18: 296: 290: 284: 268:(7): 91–97. 265: 261: 250: 215: 211: 184:. Retrieved 180:the original 172:Folding@home 171: 136:(1): 52–61. 133: 129: 123: 95:Folding@home 84: 71:Folding@home 68: 65:Applications 55: 34: 16: 15: 218:(1): 4–11. 46:phase space 326:Categories 299:: 429–52. 132:(review). 116:References 31:Background 313:22577825 242:21081274 150:22257762 89:See also 233:3042729 37:folding 311:  240:  230:  148:  52:Theory 309:PMID 238:PMID 188:2012 146:PMID 301:doi 270:doi 228:PMC 220:doi 138:doi 328:: 307:. 297:41 295:. 266:51 264:. 260:. 236:. 226:. 216:21 214:. 210:. 196:^ 174:. 170:. 158:^ 144:. 134:22 77:. 315:. 303:: 278:. 272:: 244:. 222:: 190:. 152:. 140::

Index

molecular biology
protein folding
folding
thermodynamic free energy
phase space
metastable states
Folding@home
Markov state models
Folding@home
Hidden Markov model
Computational biology
Molecular biology
doi
10.1016/j.sbi.2011.12.001
PMID
22257762


"Folding@home Simulation FAQ"
Stanford University
the original



"Taming the complexity of protein folding"
doi
10.1016/j.sbi.2010.10.006
PMC
3042729
PMID

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