scholarly journals BAR-based Optimum Adaptive Steered MD for Configurational Sampling

2018 ◽  
Author(s):  
Xiaohui Wang ◽  
Xingzhao Tu ◽  
Boming Deng ◽  
John Z. H. Zhang ◽  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Adaptive Sampling ◽  
Sampling Method ◽  
Time Derivative ◽  
Selection Criterion ◽  
Equal Time ◽  
Acceptance Ratio ◽  
Configurational Space ◽  
State Discrimination ◽  
Bennett’S Acceptance Ratio

<p>Previously we proposed the equilibrium and nonequilibrium adaptive alchemical free energy simulation methods Optimum Bennett’s Acceptance Ratio (OBAR) and Optimum Crooks’ Equation (OCE). They are based on the statistically optimal bidirectional reweighting estimator named Bennett’s Acceptance Ratio (BAR) or Crooks’ Equation (CE). They perform initial sampling in the staging alchemical transformation and then determine the importance rank of different states via the time-derivative of the variance (TDV). The method is proven to give speedups compared with the equal time rule. In the current work, we extended the time derivative of variance guided adaptive sampling method to the configurational space, falling in the term of Steered MD (SMD). The SMD approach biasing physically meaningful collective variable (CV) such as one dihedral or one distance to pulling the system from one conformational state to another. By minimizing the variance of the free energy differences along the pathway in an optimized way, a new type of adaptive SMD (ASMD) is introduced. As exhibits in the alchemical case, this adaptive sampling method outperforms the traditional equal-time SMD in nonequilibrium stratification. Also, the method gives much more efficient calculation of potential of mean force than the selection criterion based ASMD scheme, which is proven to be more efficient than traditional SMD. The variance-linearly-dependent minus time derivative of overall variance proposed for OBAR and OCE criterion is extended to determine the importance rank of the nonequilibrium pulling in the configurational space. It is shown that the importance rank given by the standard deviation of the free energy difference is wrong, but by correcting it with the simulation time we obtain the true importance rank in nonequilibrium stratification. The OCE workflow is periodicity-of-CV dependent while ASMD is not. In the non-periodic CV case, the end-state discrimination in the SD rank is eliminated in the TDV rank, while in the periodic CV case the correction introduced in the TDV rank is not that significant. The performance is demonstrated in a dihedral flipping case and two distance pulling cases, accounting for periodic and non-periodic CVs, respectively. </p>

BAR-based Optimum Adaptive Steered MD for Configurational Sampling

2019 ◽  
Author(s):  
Xiaohui Wang ◽  
Xingzhao Tu ◽  
Boming Deng ◽  
John Z. H. Zhang ◽  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Adaptive Sampling ◽  
Sampling Method ◽  
Time Derivative ◽  
Selection Criterion ◽  
Equal Time ◽  
Acceptance Ratio ◽  
Configurational Space ◽  
State Discrimination ◽  
Bennett’S Acceptance Ratio

<p>Previously we proposed the equilibrium and nonequilibrium adaptive alchemical free energy simulation methods Optimum Bennett’s Acceptance Ratio (OBAR) and Optimum Crooks’ Equation (OCE). They are based on the statistically optimal bidirectional reweighting estimator named Bennett’s Acceptance Ratio (BAR) or Crooks’ Equation (CE). They perform initial sampling in the staging alchemical transformation and then determine the importance rank of different states via the time-derivative of the variance (TDV). The method is proven to give speedups compared with the equal time rule. In the current work, we extended the time derivative of variance guided adaptive sampling method to the configurational space, falling in the term of Steered MD (SMD). The SMD approach biasing physically meaningful collective variable (CV) such as one dihedral or one distance to pulling the system from one conformational state to another. By minimizing the variance of the free energy differences along the pathway in an optimized way, a new type of adaptive SMD (ASMD) is introduced. As exhibits in the alchemical case, this adaptive sampling method outperforms the traditional equal-time SMD in nonequilibrium stratification. Also, the method gives much more efficient calculation of potential of mean force than the selection criterion based ASMD scheme, which is proven to be more efficient than traditional SMD. The variance-linearly-dependent minus time derivative of overall variance proposed for OBAR and OCE criterion is extended to determine the importance rank of the nonequilibrium pulling in the configurational space. It is shown that the importance rank given by the standard deviation of the free energy difference is wrong, but by correcting it with the simulation time we obtain the true importance rank in nonequilibrium stratification. The OCE workflow is periodicity-of-CV dependent while ASMD is not. In the non-periodic CV case, the end-state discrimination in the SD rank is eliminated in the TDV rank, while in the periodic CV case the correction introduced in the TDV rank is not that significant. The performance is demonstrated in a dihedral flipping case and two distance pulling cases, accounting for periodic and non-periodic CVs, respectively. </p>

scholarly journals BAR-based Optimum Adaptive Steered MD for Configurational Sampling

2019 ◽  
Author(s):  
Xiaohui Wang ◽  
Xingzhao Tu ◽  
Boming Deng ◽  
John Z. H. Zhang ◽  
Zhaoxi Sun
Keyword(s):  
Free Energy ◽  
Adaptive Sampling ◽  
Sampling Method ◽  
Time Derivative ◽  
Selection Criterion ◽  
Equal Time ◽  
Acceptance Ratio ◽  
Configurational Space ◽  
State Discrimination ◽  
Bennett’S Acceptance Ratio

<p>Previously we proposed the equilibrium and nonequilibrium adaptive alchemical free energy simulation methods Optimum Bennett’s Acceptance Ratio (OBAR) and Optimum Crooks’ Equation (OCE). They are based on the statistically optimal bidirectional reweighting estimator named Bennett’s Acceptance Ratio (BAR) or Crooks’ Equation (CE). They perform initial sampling in the staging alchemical transformation and then determine the importance rank of different states via the time-derivative of the variance (TDV). The method is proven to give speedups compared with the equal time rule. In the current work, we extended the time derivative of variance guided adaptive sampling method to the configurational space, falling in the term of Steered MD (SMD). The SMD approach biasing physically meaningful collective variable (CV) such as one dihedral or one distance to pulling the system from one conformational state to another. By minimizing the variance of the free energy differences along the pathway in an optimized way, a new type of adaptive SMD (ASMD) is introduced. As exhibits in the alchemical case, this adaptive sampling method outperforms the traditional equal-time SMD in nonequilibrium stratification. Also, the method gives much more efficient calculation of potential of mean force than the selection criterion based ASMD scheme, which is proven to be more efficient than traditional SMD. The variance-linearly-dependent minus time derivative of overall variance proposed for OBAR and OCE criterion is extended to determine the importance rank of the nonequilibrium pulling in the configurational space. It is shown that the importance rank given by the standard deviation of the free energy difference is wrong, but by correcting it with the simulation time we obtain the true importance rank in nonequilibrium stratification. The OCE workflow is periodicity-of-CV dependent while ASMD is not. In the non-periodic CV case, the end-state discrimination in the SD rank is eliminated in the TDV rank, while in the periodic CV case the correction introduced in the TDV rank is not that significant. The performance is demonstrated in a dihedral flipping case and two distance pulling cases, accounting for periodic and non-periodic CVs, respectively. </p>

scholarly journals The Good, the Bad, and the Ugly: “HiPen”, a New Dataset for Validating (S)QM/MM Free Energy Simulations

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 681 ◽  
Author(s):  
Fiona Kearns ◽  
Luke Warrensford ◽  
Stefan Boresch ◽  
H. Woodcock
Keyword(s):  
Free Energy ◽  
Gas Phase ◽  
Convergence Criteria ◽  
Free Energies ◽  
Acceptance Ratio ◽  
Current State ◽  
Energy Perturbation ◽  
Energy Simulations ◽  
Molecular Description ◽  
Bennett’S Acceptance Ratio

Indirect (S)QM/MM free energy simulations (FES) are vital to efficiently incorporating sufficient sampling and accurate (QM) energetic evaluations when estimating free energies of practical/experimental interest. Connecting between levels of theory, i.e., calculating Δ A l o w → h i g h , remains to be the most challenging step within an indirect FES protocol. To improve calculations of Δ A l o w → h i g h , we must: (1) compare the performance of all FES methods currently available; and (2) compile and maintain datasets of Δ A l o w → h i g h calculated for a wide-variety of molecules so that future practitioners may replicate or improve upon the current state-of-the-art. Towards these two aims, we introduce a new dataset, “HiPen”, which tabulates Δ A g a s M M → 3 o b (the free energy associated with switching from an M M to an S C C − D F T B molecular description using the 3ob parameter set in gas phase), calculated for 22 drug-like small molecules. We compare the calculation of this value using free energy perturbation, Bennett’s acceptance ratio, Jarzynski’s equation, and Crooks’ equation. We also predict the reliability of each calculated Δ A g a s M M → 3 o b by evaluating several convergence criteria including sample size hysteresis, overlap statistics, and bias metric ( Π ). Within the total dataset, three distinct categories of molecules emerge: the “good” molecules, for which we can obtain converged Δ A g a s M M → 3 o b using Jarzynski’s equation; “bad” molecules which require Crooks’ equation to obtain a converged Δ A g a s M M → 3 o b ; and “ugly” molecules for which we cannot obtain reliably converged Δ A g a s M M → 3 o b with either Jarzynski’s or Crooks’ equations. We discuss, in depth, results from several example molecules in each of these categories and describe how dihedral discrepancies between levels of theory cause convergence failures even for these gas phase free energy simulations.

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