Anton, a special-purpose machine for molecular dynamics simulation

Shaw, David E.; Deneroff, Martin M.; Dror, Ron O.; Kuskin, Jeffrey S.; Larson, Richard H.; Salmon, John K.; Young, Cliff; Batson, Brannon; Bowers, K. J.; Chao, Jack C.; Eastwood, Michael P.; Gagliardo, Joseph; Grossman, J. P.; Ho, C. Richard; Ierardi, Douglas J.; Kolossváry, István; Klepeis, John L.; Layman, Timothy; McLeavey, Christine; Moraes, Mark A.; Mueller, Rolf; Priest, Edward C.; Shan, Yibing; Spengler, Jochen; Theobald, Michael; Towles, Brian; Wang, Stanley C.

doi:10.1145/1273440.1250664

Cited by 154 publications

(111 citation statements)

References 35 publications

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“…A truly quantitative connection to these measurements requires modeling the equilibrium ensemble. Finally, recent advances in atomistic simulation (34,43,44,45), special-purpose hardware (46), and distributed computing analysis (47,48) have enabled atomistic simulations to reach the millisecond timescale (49,50,51,52); the computational cost of ensemble modeling is quickly becoming manageable.…”

Section: Discussion Structural Ensemble Biologymentioning

confidence: 99%

Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

Beauchamp¹,

Pande²,

Das³

2014

Preprint

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Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian Energy Landscape Tilting (BELT) scheme for computing Bayesian "hyperensembles" over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and 3 J measurements gives convergent values of the peptide's α, β, and P P II conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data.

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Section: Discussion Structural Ensemble Biologymentioning

confidence: 99%

Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

Beauchamp¹,

Pande²,

Das³

2014

Preprint

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“…All-atom MD simulations were performed in explicit solvent using the TIP3P water model (38). The simulations were carried out both on general-purpose supercomputers using NAMD 2.8 (39) and on the special-purpose supercomputer Anton (40). All simulations were carried out with periodic boundary conditions in constant particle number, temperature and pressure ensemble.…”

Section: Methodsmentioning

confidence: 99%

Misplaced helix slows down ultrafast pressure-jump protein folding

Prigozhin¹,

Liu²,

Wirth³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Using a newly developed microsecond pressure-jump apparatus, we monitor the refolding kinetics of the helix-stabilized five-helix bundle protein λ*YA, the Y22W/Q33Y/G46,48A mutant of λ-repressor fragment 6-85, from 3 μs to 5 ms after a 1,200-bar P-drop. In addition to a microsecond phase, we observe a slower 1.4-ms phase during refolding to the native state. Unlike temperature denaturation, pressure denaturation produces a highly reversible helix-coilrich state. This difference highlights the importance of the denatured initial condition in folding experiments and leads us to assign a compact nonnative helical trap as the reason for slower P-jumpinduced refolding. To complement the experiments, we performed over 50 μs of all-atom molecular dynamics P-drop refolding simulations with four different force fields. Two of the force fields yield compact nonnative states with misplaced α-helix content within a few microseconds of the P-drop. Our overall conclusion from experiment and simulation is that the pressure-denatured state of λ*YA contains mainly residual helix and little β-sheet; following a fast P-drop, at least some λ*YA forms misplaced helical structure within microseconds. We hypothesize that nonnative helix at helix-turn interfaces traps the protein in compact nonnative conformations. These traps delay the folding of at least some of the population for 1.4 ms en route to the native state. Based on molecular dynamics, we predict specific mutations at the helix-turn interfaces that should speed up refolding from the pressure-denatured state, if this hypothesis is correct.downhill folding | fluorescence lifetime | molecular dynamics simulation | thermal denaturation | lambda repressor T emperature and pressure are excellent perturbations when comparing experimental folding kinetics with molecular dynamics (MD) simulations (1). Fast temperature-jumps (T-jumps) and pressure-jumps (P-jumps) are relatively easy to simulate by MD. Typical temperature changes required to cross the protein folding transition are 5-20 K, easily implemented with laser T-jumps (2). Typical pressure changes required to cross the folding transition are 1-5 kbar, previously achieved only with millisecond time resolution (piezo methods are limited to ΔP < 100 bar) (3, 4). We recently reported a P-jump instrument capable of >1-kbar P-drops with ∼1-μs dead time (5).Folded proteins have a larger partial molar volume than pressure-denatured proteins (by about 10 1 -10 2 mL/mol) (6). The fractal dimension of their folded state is less than 3 because voids occur whenever a connected chain made from a finite amino acid alphabet is packed into a compact structure (7,8). Such imperfections in packing, which disappear when small water molecules solvate the polypeptide chain, lead to protein unfolding under pressure (9). Pressure unfolding is a slow process because the positive activation volume is unfavorable at high pressure (10).Here, we study the much faster process of protein refolding at 1 bar and room temperature, starting from the pressure-d...

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“…Their small size makes them attractive for investigation using statistical mechanical models that enumerate conformations and therefore provide a comprehensive description of the kinetics by solving the set of differential equations for the time course of each conformation (16)(17)(18)(19). Finally, with recent improvements in computing power and the application of distributed computing (20)(21)(22), their size and folding speed allows the kinetics and mechanisms of folding to be studied by atomistic molecular dynamics simulations.…”

mentioning

confidence: 99%

Making connections between ultrafast protein folding kinetics and molecular dynamics simulations

Cellmer

Buscaglia

Henry

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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Determining the rate of forming the truly folded conformation of ultrafast folding proteins is an important issue for both experiments and simulations. The double-norleucine mutant of the 35-residue villin subdomain is the focus of recent computer simulations with atomistic molecular dynamics because it is currently the fastest folding protein. The folding kinetics of this protein have been measured in laser temperature-jump experiments using tryptophan fluorescence as a probe of overall folding. The conclusion from the simulations, however, is that the rate determined by fluorescence is significantly larger than the rate of overall folding. We have therefore employed an independent experimental method to determine the folding rate. The decay of the tryptophan triplet-state in photoselection experiments was used to monitor the change in the unfolded population for a sequence of the villin subdomain with one amino acid difference from that of the laser temperature-jump experiments, but with almost identical equilibrium properties. Folding times obtained in a two-state analysis of the results from the two methods at denaturant concentrations varying from 1.5-6.0 M guanidinium chloride are in excellent agreement, with an average difference of only 20%. Polynomial extrapolation of all the data to zero denaturant yields a folding time of 220 ðþ100, − 70Þ ns at 283 K, suggesting that under these conditions the barrier between folded and unfolded states has effectively disappeared-the so-called "downhill scenario." tryptophan triplet lifetime | villin headpiece subdomain | downhill protein folding | laser temperature jump

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Anton, a special-purpose machine for molecular dynamics simulation

Cited by 154 publications

References 35 publications

Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles

Misplaced helix slows down ultrafast pressure-jump protein folding

Making connections between ultrafast protein folding kinetics and molecular dynamics simulations

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