Millisecond-scale molecular dynamics simulations on Anton

Shaw, David E.; Bowers, K. J.; Chow, Edmond; Eastwood, Michael P.; Ierardi, Douglas J.; Klepeis, John L.; Kuskin, Jeffrey S.; Larson, Richard H.; Lindorff‐Larsen, Kresten; Maragakis, Paul; Moraes, Mark A.; Dror, Ron O.; Piana, Stefano; Shan, Yibing; Towles, Brian; Salmon, John K.; Grossman, J. P.; MacKenzie, Kenneth; Bank, Joseph A.; Young, Cliff; Deneroff, Martin M.; Batson, Brannon

doi:10.1145/1654059.1654126

Cited by 311 publications

(156 citation statements)

References 31 publications

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“…Relaxation dispersion measurements provide a high level of detail into the populations, exchange correlation times, and chemical shift differences between two states (3)(4)(5). Until recently, visualizing the specific structural implications of these dispersion measurements has been limited to comparisons with static crystal structures or models, because the slow timescale of these motions was beyond the reach of atomistic molecular simulation (6,7).…”

Section: Introductionmentioning

confidence: 99%

Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A

Schiffer

Feher

Malmstrom

et al. 2016

Biophysical Journal

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Proteins commonly sample a number of conformational states to carry out their biological function, often requiring transitions from the ground state to higher-energy states. Characterizing the mechanisms that guide these transitions at the atomic level promises to impact our understanding of functional protein dynamics and energy landscapes. The leucine-99-toalanine (L99A) mutant of T4 lysozyme is a model system that has an experimentally well characterized excited sparsely populated state as well as a ground state. Despite the exhaustive study of L99A protein dynamics, the conformational changes that permit transitioning to the experimentally detected excited state (~3%, DG~2 kcal/mol) remain unclear. Here, we describe the transitions from the ground state to this sparsely populated excited state of L99A as observed through a single molecular dynamics (MD) trajectory on the Anton supercomputer. Aside from detailing the ground-to-excited-state transition, the trajectory samples multiple metastates and an intermediate state en route to the excited state. Dynamic motions between these states enable cavity surface openings large enough to admit benzene on timescales congruent with known rates for benzene binding. Thus, these fluctuations between rare protein states provide an atomic description of the concerted motions that illuminate potential path(s) for ligand binding. These results reveal, to our knowledge, a new level of complexity in the dynamics of buried cavities and their role in creating mobile defects that affect protein dynamics and ligand binding.

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Section: Introductionmentioning

confidence: 99%

Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A

Schiffer

Feher

Malmstrom

et al. 2016

Biophysical Journal

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“…The MD technique with a general-purpose graphics processing unit (GPGPU) (Götz et al 2012;Mashimo et al 2013;Pall et al 2014;SalomonFerrer et al 2013) is growing in importance due to multiple processors being less expensive than CPUs. Hardware architectures specialized for MD, such as Anton (Shaw et al 2009) and MD-GRAPE (Narumi et al 2006), have enabled extremely long-time scale MD simulations (Kikugawa et al 2009;Lindorff-Larsen et al 2011;Shaw et al 2010). These specialized architectures speed up a single MD simulation run and provide an increased number of conformations from the long MD trajectory.…”

Section: Trivial Trajectory Parallelization Of Mcmdmentioning

confidence: 99%

Enhanced sampling simulations to construct free-energy landscape of protein–partner substrate interaction

2016

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Molecular dynamics (MD) simulations using allatom and explicit solvent models provide valuable information on the detailed behavior of protein-partner substrate binding at the atomic level. As the power of computational resources increase, MD simulations are being used more widely and easily. However, it is still difficult to investigate the thermodynamic properties of protein-partner substrate binding and protein folding with conventional MD simulations. Enhanced sampling methods have been developed to sample conformations that reflect equilibrium conditions in a more efficient manner than conventional MD simulations, thereby allowing the construction of accurate free-energy landscapes. In this review, we discuss these enhanced sampling methods using a series of case-by-case examples. In particular, we review enhanced sampling methods conforming to trivial trajectory parallelization, virtual-system coupled multicanonical MD, and adaptive lambda square dynamics. These methods have been recently developed based on the existing method of multicanonical MD simulation. Their applications are reviewed with an emphasis on describing their practical implementation. In our concluding remarks we explore extensions of the enhanced sampling methods that may allow for even more efficient sampling.

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“…Given the efficiency and precision with which proteins carry out their missions, they are also being explored from the technological point of view. The applications of proteins even outside the biological realm are many if we could harness their power [1], and molecular dynamics simulations of great complexity and scale are being done in many laboratories around the world as a tool to understand them [4,31,32].…”

Section: Proteinsmentioning

confidence: 99%

“…In addition to this, since biologically interesting molecules (like proteins [1] and DNA [2]) consist of thousands of atoms, their trajectories in configuration space are esentially chaotic, and therefore reliable quantities can be obtained from the simulation only after statistical analysis [3]. In order to cope with these two requirements, which force the computation of a large number of dynamical steps if predictions want to be made, great efforts are being done both in hardware [4,5] and in software [6,7] solutions. In fact, only in very recent times, simulations for interesting systems of hundreds of thousand of atoms in the millisecond scale are starting to become affordable, being still, as we mentioned, the main limitation of these computational techniques the large difference between the elemental time step used to integrate the equations of motion and the total time span needed to obtain useful information.…”

Section: Introductionmentioning

confidence: 99%

Exact and efficient calculation of lagrange multipliers in biological polymers with constrained bond lengths and bond angles: Proteins and nucleic acids as example cases

2011

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In order to accelerate molecular dynamics simulations, it is very common to impose holonomic constraints on their hardest degrees of freedom. In this way, the time step used to integrate the equations of motion can be increased, thus allowing, in principle, to reach longer total simulation times. The imposition of such constraints results in an aditional set of N c equations (the equations of constraint) and unknowns (their associated Lagrange multipliers), that must be solved in one way or another at each time step of the dynamics. In this work it is shown that, due to the essentially linear structure of typical biological polymers, such as nucleic acids or proteins, the algebraic equations that need to be solved involve a matrix which is banded if the constraints are indexed in a clever way. This allows to obtain the Lagrange multipliers through a non-iterative procedure, which can be considered exact up to machine precision, and which takes O(N c ) operations, instead of the usual O(N 3 c ) for generic molecular systems. We develop the formalism, and describe the appropriate indexing for a number of model molecules and also for alkanes, proteins and DNA. Finally, we provide a numerical example of * Email: garcia.risueno@gmail.com the technique in a series of polyalanine peptides of different lengths using the AMBER molecular dynamics package.

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Millisecond-scale molecular dynamics simulations on Anton

Cited by 311 publications

References 31 publications

Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A

Capturing Invisible Motions in the Transition from Ground to Rare Excited States of T4 Lysozyme L99A

Enhanced sampling simulations to construct free-energy landscape of protein–partner substrate interaction

Exact and efficient calculation of lagrange multipliers in biological polymers with constrained bond lengths and bond angles: Proteins and nucleic acids as example cases

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