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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"
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73:distributed computing project in combination with
27:when coupled with molecular dynamics simulations.
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208:"Taming the complexity of protein folding"
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206:G. Bowman; V. Volez; V. S. Pande (2011).
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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
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347:Mathematical and theoretical biology
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69:Adaptive sampling is used by the
56:If a protein folds through the
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168:"Folding@home Simulation FAQ"
292:Annual Review of Biophysics
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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
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186:September 10,
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268:(7): 91–97.
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184:. Retrieved
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172:Folding@home
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95:Folding@home
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71:Folding@home
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65:Applications
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218:(1): 4–11.
46:phase space
326:Categories
299:: 429–52.
132:(review).
116:References
31:Background
313:22577825
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89:See also
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52:Theory
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188:2012
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301:doi
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228:PMC
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