Comparison of efficiency and bias of free energies computed by exponential averaging, the Bennett acceptance ratio, and thermodynamic integration

2005 ◽  
Vol 122 (14) ◽  
pp. 144107 ◽  
Author(s):  
Michael R. Shirts ◽  
Vijay S. Pande
Keyword(s):  
Thermodynamic Integration ◽  
Free Energies ◽  
Acceptance Ratio ◽  
Bennett Acceptance Ratio

Understanding defects in DSA: calculation of free energies of block copolymer DSA systems via thermodynamic integration of a mesoscale block-copolymer model

2014 ◽  
Author(s):  
Andrew J. Peters ◽  
Richard A. Lawson ◽  
Benjamin D. Nation ◽  
Peter J. Ludovice ◽  
Clifford L. Henderson
Keyword(s):  
Block Copolymer ◽  
Thermodynamic Integration ◽  
Free Energies

scholarly journals Multiensemble Markov models of molecular thermodynamics and kinetics

2016 ◽  
Vol 113 (23) ◽  
pp. E3221-E3230 ◽  
Author(s):  
Hao Wu ◽  
Fabian Paul ◽  
Christoph Wehmeyer ◽  
Frank Noé
Keyword(s):  
Detailed Balance ◽  
Rare Event ◽  
Umbrella Sampling ◽  
High Dimensional ◽  
Acceptance Ratio ◽  
Markov State ◽  
Markov State Models ◽  
Bennett Acceptance Ratio ◽  
Special Cases ◽  
State Models

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models—clustering of high-dimensional spaces and modeling of complex many-state systems—with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein–ligand binding model.

Use of thermodynamic integration to calculate the hydration free energies of n-alkanes

2002 ◽  
Vol 116 (6) ◽  
pp. 2361-2369 ◽  
Author(s):  
J. T. Wescott ◽  
L. R. Fisher ◽  
S. Hanna
Keyword(s):  
Thermodynamic Integration ◽  
Free Energies

scholarly journals Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility

2021 ◽  
Author(s):  
Alexander Wade ◽  
Agastya Bhati ◽  
Shunzhou Wan ◽  
Peter Coveney
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Thermodynamic Integration ◽  
Free Energy Perturbation ◽  
Free Energies ◽  
Ensemble Averaging ◽  
Relative Binding ◽  
Energy Perturbation ◽  
Binding Free Energies

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat myriad diseases. In this work we examine the computation of alchemical relative binding free energies with an eye to assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2 and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2 and NAMD3. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between packages of 0.5 $kcal/mol$ The correlation between packages is very good with the lowest Spearman's, Pearson's and Kendall's tau correlation coefficient between two packages being 0.91, 0.89 and 0.74 respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.

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