Local elevation: A method for improving the searching properties of molecular dynamics simulation

Huber, Thomas; Torda, Andrew E.; Gunsteren, Wilfred F. van

doi:10.1007/bf00124016

Cited by 549 publications

(533 citation statements)

References 16 publications

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“…Here, we have developed a general adaptive boost formalism based on previous developments [2][3][4][5][6][7][8] . Given a uncharacterized V (r), we first evaluate the smooth histogram ρ(A) of collective variables (CVs) 9,10 A ≡ {A 1 (r), · · · , A M (r)} by MD, and then utilize the smooth histogram (probability density) of A as the boost potential ∆V (r) ∝ k B T ln ρ(A) (1) in subsequent accelerated MD simulations.…”

Section: Adaptive Boost Methodsmentioning

confidence: 99%

Adaptive-boost molecular dynamics simulation of carbon diffusion in iron

et al. 2012

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We have developed an accelerated molecular dynamics (MD) method to model atomic-scale rare events. In this method, a smooth histogram of collective variables is first estimated by canonical ensemble molecular dynamics calculations, and then a temperature-dependent boost potential is iteratively constructed to accelerate the MD simulation. This method not only allows us to observe the rare events but also to evaluate the profile of free energy and trial frequency along the reaction coordinate. We employed this method to study carbon diffusion in BCC iron and evaluated carbon's temperature-dependent diffusivity. The obtained diffusivities agree well with the experimental measurements. Even at low temperature for which no experimental data are available, the diffusivity can be evaluated accurately. Additionally, we study carbon diffusion inside edge dislocation core in BCC iron, and demonstrate the applicability of the method to rare events on a rugged free energy surface.

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Section: Adaptive Boost Methodsmentioning

confidence: 99%

Adaptive-boost molecular dynamics simulation of carbon diffusion in iron

et al. 2012

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“…Several methods are available to study chemical reactions, including static quantum approaches or even advanced sampling techniques, e.g., umbrella sampling [21], metadynamics [22][23][24], and parallel tempering [25]. In this work, the reaction mechanism was explored using the static quantum approach [26].…”

Section: Theoretical Calculationsmentioning

confidence: 99%

The mechanism of formate oxidation by metal-dependent formate dehydrogenases

et al. 2011

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Metal-dependent formate dehydrogenases (Fdh) from prokaryotic organisms are members of the dimethyl sulfoxide reductase family of mononuclear molybdenum-containing and tungsten-containing enzymes. Fdhs catalyze the oxidation of the formate anion to carbon dioxide in a redox reaction that involves the transfer of two electrons from the substrate to the active site. The active site in the oxidized state comprises a hexacoordinated molybdenum or tungsten ion in a distorted trigonal prismatic geometry. Using this structural model, we calculated the catalytic mechanism of Fdh through density functional theory tools. The simulated mechanism was correlated with the experimental kinetic properties of three different Fdhs isolated from three different Desulfovibrio species. Our studies indicate that the C-H bond break is an event involved in the rate-limiting step of the catalytic cycle. The role in catalysis of conserved amino acid residues involved in metal coordination and near the metal active site is discussed on the basis of experimental and theoretical results.

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“…This iterative approach to the problem 28,29 led to the development of adaptive biasing potential methods that improve the potential "on the fly", 16,17,19,30 i.e., while the simulation is performed. All these methods share the common basic idea, namely, "to introduce the concept of memory" 30 during a simulation by changing the potential of mean force perceived by the system, in order to penalize conformations that have been already sampled before.…”

Section: Metadynamics Simulation: History-dependent Algorithms In Nonmentioning

confidence: 99%

ORAC: A molecular dynamics simulation program to explore free energy surfaces in biomolecular systems at the atomistic level

et al. 2009

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Abstract:We present the new release of the ORAC engine (Procacci et al., Comput Chem 1997, 18, 1834, a FORTRAN suite to simulate complex biosystems at the atomistic level. The previous release of the ORAC code included multiple time steps integration, smooth particle mesh Ewald method, constant pressure and constant temperature simulations. The present release has been supplemented with the most advanced techniques for enhanced sampling in atomistic systems including replica exchange with solute tempering, metadynamics and steered molecular dynamics. All these computational technologies have been implemented for parallel architectures using the standard MPI communication protocol. ORAC is an open-source program distributed free of charge under the GNU general public license (GPL) at

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Local elevation: A method for improving the searching properties of molecular dynamics simulation

Cited by 549 publications

References 16 publications

Adaptive-boost molecular dynamics simulation of carbon diffusion in iron

Adaptive-boost molecular dynamics simulation of carbon diffusion in iron

The mechanism of formate oxidation by metal-dependent formate dehydrogenases

ORAC: A molecular dynamics simulation program to explore free energy surfaces in biomolecular systems at the atomistic level

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