Statistically optimal analysis of samples from multiple equilibrium states

Shirts, Michael R.; Chodera, John D.

doi:10.1063/1.2978177

Cited by 1,629 publications

(2,473 citation statements)

References 33 publications

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“…3 vanish. Free energies were also calculated by multi-state BAR [40], thermodynamic integration [41], and exponential averaging [42]. We employed 13 states in these calculations (λ = 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, and 0.99; for technical reasons, AMBER does not allow calculations at λ = 0.00 and 1.00).…”

Section: Fep Calculationsmentioning

confidence: 99%

Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host–guest binding energies

Mikulskis

Cioloboc

Andrejić

et al. 2014

J Comput Aided Mol Des

220

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Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid hostguest binding energies. Link to publication Citation for published version (APA): Mikulskis, P., Cioloboc, D., Andrejić, M., Khare, S., Brorsson, J., Genheden, S., ... Ryde, U. (2014). Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host-guest binding energies. Journal of Computer-Aided Molecular Design, 28(4), 375-400. DOI: 10.1007/s10822-014-9739-x General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal AbstractWe have estimated free energies for the binding of nine cyclic carboxylate guest molecules to the octa-acid host in the SAMPL4 blind-test challenge with four different approaches. First, we used standard free-energy perturbation calculations of relative binding affinities, performed at the molecular-mechanics (MM) level with TIP3P waters, the GAFF force field, and two different sets of charges for the host and the guest, obtained either with the restrained electrostatic potential or AM1-BCC methods. Both charge sets give good and nearly identical results, with a mean absolute deviation (MAD) of 4 kJ/mol and a correlation coefficient (R 2 ) of 0.8 compared to experimental results. Second, we tried to improve these predictions with 28 800 density-functional theory (DFT) calculations for selected snapshots and the non-Boltzmann Bennett acceptance-ratio method, but this led to much worse results, probably because of a too large difference between the MM and DFT potential-energy functions. Third, we tried to calculate absolute affinities using minimised DFT structures. This gave intermediate-quality results with MADs of 5-9 kJ/mol and R 2 = 0.6-0.8, depending on how the structures were obtained. Finally, we tried to improve these results using local coupled-cluster calculations with single and double excitations, and non-iterative perturbative treatment of triple excitations (LCCSD(T0)), employing the polarisable multipole interactions with supermolecular pairs approach. Unfortunately, this only degraded the predictions, probably because a mismatch between the solvation energies obtained at the DFT and LCCSD(T0) levels.Key Words: binding affinities, host-guest, free-energies perturbation, density-functional calculations, CCSD(T), polarisable multipole interactions. 2 IntroductionOne of the largest challenges of computational chemistry is to predict the binding affinity of a small ligand to a larger receptor molecule, e.g. a drug candidate to its receptor prot...

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Section: Fep Calculationsmentioning

confidence: 99%

Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host–guest binding energies

Mikulskis

Cioloboc

Andrejić

et al. 2014

J Comput Aided Mol Des

220

View full text Add to dashboard Cite

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“…[23]. Note that only the differences of the dimensionless free energies are meaningful as the absolute valuesf i are determined up to an additive constant and that the "hat" indicates MBAR estimates for the dimensionless free energies, to be distinguished from the exact (reference) values.…”

Section: Computing High-dimensional Volumesmentioning

confidence: 99%

“…with a different reduced potential function) without any additional iterative solution of the self-consistent estimating equations, see Ref. [23] for details.…”

Section: Computing High-dimensional Volumesmentioning

confidence: 99%

“…The MBAR method [23] is a binless and statistically optimal estimator to compute the difference in dimensionless free energy for multiple sets of equilibrium states (trajectories) {x} i obtained using different biasing potentials u i (x). The difference in dimensionless free energy is defined as…”

Section: Computing High-dimensional Volumesmentioning

confidence: 99%

“…All the above methods can be used to compute high-dimensional volumes. However, the choice of the MBAR method [23] is an optimal one. Not only is MBAR non-parametric (no binning is required) and has the lowest known variance reweighting estimator for free energy calculations, but it also eliminates the need for explicit numerical integration of the density of states, thus reducing to a minimum the number of systematic biases.…”

Section: Introductionmentioning

confidence: 99%

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We propose an efficient Monte Carlo method for the computation of the volumes of highdimensional bodies with arbitrary shape. We start with a region of known volume within the interior of the manifold and then use the multi-state Bennett acceptance-ratio method to compute the dimensionless free-energy difference between a series of equilibrium simulations performed within this object. The method produces results that are in excellent agreement with thermodynamic integration, as well as a direct estimate of the associated statistical uncertainties. The histogram method also allows us to directly obtain an estimate of the interior radial probability density profile, thus yielding useful insight into the structural properties of such a high dimensional body. We illustrate the method by analysing the effect of structural disorder on the basins of attraction of mechanically stable packings of soft repulsive spheres.

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Statistically optimal analysis of samples from multiple equilibrium states

Cited by 1,629 publications

References 33 publications

Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host–guest binding energies

Free-energy perturbation and quantum mechanical study of SAMPL4 octa-acid host–guest binding energies

Structural analysis of high-dimensional basins of attraction

Understanding Enzyme Catalysis Using Computer Simulation

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