2003
DOI: 10.1063/1.1590311
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Free energy calculation from steered molecular dynamics simulations using Jarzynski’s equality

Abstract: Jarzynski's equality is applied to free energy calculations from steered molecular dynamics simulations of biomolecules. The helix-coil transition of deca-alanine in vacuum is used as an example. With about ten trajectories sampled, the second order cumulant expansion, among the various averaging schemes examined, yields the most accurate estimates. We compare umbrella sampling and the present method, and find that their efficiencies are comparable.

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Cited by 753 publications
(1,017 citation statements)
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References 33 publications
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“…The free energy calculation was based on Jarzynski's equality and the stiff-spring approximation described by Park and Schulten. 29 The free energy was calculated based on the first order cumulant expansion formula, the second order cumulant expansion formula, and the full exponential formula. The convergence of the free energy curves derived from the second order cumulant and the full exponential formula was used as an indication that the work distribution is Gaussian.…”
Section: Simulation Detailsmentioning
confidence: 99%
“…The free energy calculation was based on Jarzynski's equality and the stiff-spring approximation described by Park and Schulten. 29 The free energy was calculated based on the first order cumulant expansion formula, the second order cumulant expansion formula, and the full exponential formula. The convergence of the free energy curves derived from the second order cumulant and the full exponential formula was used as an indication that the work distribution is Gaussian.…”
Section: Simulation Detailsmentioning
confidence: 99%
“…Figure 5 plots the gradient of the estimated PMF using the various work paths and directly using the relation given in Equation 14 (the inset plots the raw PMF). The dashed lines in the plots correspond to the PMF estimated from 100 copies estimated along a single (estimated) diffusion model; the solid black line corresponds to that of pooling the work paths from all synthetic trajectories together and then estimating the resulting PMF through evaluating the empirical exponential average and the solid red line plots the "exact" results [3]. We could easily increase the number of synthetic paths in an attempt to (at a relatively cheap computational cost) to create a larger number of synthetic trajectories in an attempt to get the large sample sizes needed to safely calculate an exponential average; however, a major point of this paper is that it more important to characterize the distribution of SDE coefficient functions than it is to sample the work paths that come from a small set of estimated SDEs.…”
Section: B Synthetic Work and Approximating The Pmfmentioning
confidence: 99%
“…The goal is to obtain a stochastic differential equation (SDE), with nonlinear coefficient functions, that accurately describes the dynamics of a single trajectory associated with the time series output of a steered molecular dynamics (SMD) simulation. The system used to illustrate the approach is the well-studied example of using constant velocity SMD to simulate the unravelling (in vacuum) of deca-alanine at constant temperature (extensive simulation results exist for this system because it is a "fast-folder" [3]). …”
Section: Introductionmentioning
confidence: 99%
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“…This could be alleviated by pulling at a slower speed that approaches the fully reversible regime, but the optimal speed is estimated to be about 0.0001 Å/ps. 39 Such a simulation would require more than 500 ns of total simulation time. Given the availability of a reaction path from the forward SMD runs, it is possible to apply umbrella sampling techniques to extract the PMF without multiple SMD pulls.…”
Section: Umbrella Samplingmentioning
confidence: 99%