Designing Free Energy Surfaces That Match Experimental Data with Metadynamics

White, Andrew D.; Dama, James F.; Voth, Gregory A.

doi:10.1021/acs.jctc.5b00178

Title: Designing Free Energy Surfaces That Match Experimental Data with Metadynamics

Journal Article · Thu Apr 30 00:00:00 EDT 2015 · Journal of Chemical Theory and Computation

DOI:https://doi.org/10.1021/acs.jctc.5b00178· OSTI ID:1329576

White, Andrew D. ^[1]; Dama, James F. ^[1]; Voth, Gregory A. ^[1]

Univ. of Chicago, IL (United States). James Franck Inst. and Inst. for Biophysical Dynamics and Computation Inst.; Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Center for Nonlinear Studies

Creating models that are consistent with experimental data is essential in molecular modeling. This is often done by iteratively tuning the molecular force field of a simulation to match experimental data. An alternative method is to bias a simulation, leading to a hybrid model composed of the original force field and biasing terms. Previously we introduced such a method called experiment directed simulation (EDS). EDS minimally biases simulations to match average values. We also introduce a new method called experiment directed metadynamics (EDM) that creates minimal biases for matching entire free energy surfaces such as radial distribution functions and phi/psi angle free energies. It is also possible with EDM to create a tunable mixture of the experimental data and free energy of the unbiased ensemble with explicit ratios. EDM can be proven to be convergent, and we also present proof, via a maximum entropy argument, that the final bias is minimal and unique. Examples of its use are given in the construction of ensembles that follow a desired free energy. Finally, the example systems studied include a Lennard-Jones fluid made to match a radial distribution function, an atomistic model augmented with bioinformatics data, and a three-component electrolyte solution where ab initio simulation data is used to improve a classical empirical model.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1329576

Report Number(s):: LA-UR-15-21325

Journal Information:: Journal of Chemical Theory and Computation, Vol. 11, Issue 6; ISSN 1549-9618

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 41 works

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References (53)

Escaping free-energy minima Laio, A.; Parrinello, M. Proceedings of the National Academy of Sciences, Vol. 99, Issue 20 https://doi.org/10.1073/pnas.202427399	journal	September 2002
Determination of Protein Structures Consistent with NMR Order Parameters Best, Robert B.; Vendruscolo, Michele Journal of the American Chemical Society, Vol. 126, Issue 26 https://doi.org/10.1021/ja0396955	journal	July 2004
Structural Refinement from Restrained-Ensemble Simulations Based on EPR/DEER Data: Application to T4 Lysozyme Islam, Shahidul M.; Stein, Richard A.; Mchaourab, Hassane S. The Journal of Physical Chemistry B, Vol. 117, Issue 17 https://doi.org/10.1021/jp311723a	journal	April 2013
Characterization of the Interdomain Motions in Hen Lysozyme Using Residual Dipolar Couplings as Replica-Averaged Structural Restraints in Molecular Dynamics Simulations De Simone, Alfonso; Montalvao, Rinaldo W.; Dobson, Christopher M. Biochemistry, Vol. 52, Issue 37 https://doi.org/10.1021/bi4007513	journal	September 2013
Simultaneous determination of protein structure and dynamics Lindorff-Larsen, Kresten; Best, Robert B.; DePristo, Mark A. Nature, Vol. 433, Issue 7022 https://doi.org/10.1038/nature03199	journal	January 2005
On the Use of Experimental Observations to Bias Simulated Ensembles Pitera, Jed W.; Chodera, John D. Journal of Chemical Theory and Computation, Vol. 8, Issue 10 https://doi.org/10.1021/ct300112v	journal	March 2012
On the statistical equivalence of restrained-ensemble simulations with the maximum entropy method Roux, Benoît; Weare, Jonathan The Journal of Chemical Physics, Vol. 138, Issue 8 https://doi.org/10.1063/1.4792208	journal	February 2013
Efficient and Minimal Method to Bias Molecular Simulations with Experimental Data White, Andrew D.; Voth, Gregory A. Journal of Chemical Theory and Computation, Vol. 10, Issue 8 https://doi.org/10.1021/ct500320c	journal	July 2014
Combining Experiments and Simulations Using the Maximum Entropy Principle Boomsma, Wouter; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, Kresten PLoS Computational Biology, Vol. 10, Issue 2 https://doi.org/10.1371/journal.pcbi.1003406	journal	February 2014
A Simple and Fast Approach for Predicting ¹ H and ¹³ C Chemical Shifts: Toward Chemical Shift-Guided Simulations of RNA Frank, Aaron T.; Law, Sean M.; Brooks, Charles L. The Journal of Physical Chemistry B, Vol. 118, Issue 42 https://doi.org/10.1021/jp508342x	journal	October 2014
Computational challenges for macromolecular structure determination by X-ray crystallography and solution NMRspectroscopy Brünger, Axel T.; Nilges, Michael Quarterly Reviews of Biophysics, Vol. 26, Issue 1 https://doi.org/10.1017/S0033583500003966	journal	February 1993
Methods of NMR structure refinement: molecular dynamics simulations improve the agreement with measured NMR data of a C-terminal peptide of GCN4-p1 Dolenc, Jožica; Missimer, John H.; Steinmetz, Michel O. Journal of Biomolecular NMR, Vol. 47, Issue 3 https://doi.org/10.1007/s10858-010-9425-9	journal	June 2010
Molecular dynamics flexible fitting: A practical guide to combine cryo-electron microscopy and X-ray crystallography Trabuco, Leonardo G.; Villa, Elizabeth; Schreiner, Eduard Methods, Vol. 49, Issue 2 https://doi.org/10.1016/j.ymeth.2009.04.005	journal	October 2009
Cryo-Electron Microscopy Modeling by the Molecular Dynamics Flexible Fitting Method Chan, Kwok-Yan; Trabuco, Leonardo G.; Schreiner, Eduard Biopolymers, Vol. 97, Issue 9 https://doi.org/10.1002/bip.22042	journal	June 2012
Symmetry-Restrained Flexible Fitting for Symmetric EM Maps Chan, Kwok-Yan; Gumbart, James; McGreevy, Ryan Structure, Vol. 19, Issue 9 https://doi.org/10.1016/j.str.2011.07.017	journal	September 2011
Inference of Structure Ensembles of Flexible Biomolecules from Sparse, Averaged Data Olsson, Simon; Frellsen, Jes; Boomsma, Wouter PLoS ONE, Vol. 8, Issue 11 https://doi.org/10.1371/journal.pone.0079439	journal	November 2013
SAXS Ensemble Refinement of ESCRT-III CHMP3 Conformational Transitions Różycki, Bartosz; Kim, Young C.; Hummer, Gerhard Structure, Vol. 19, Issue 1 https://doi.org/10.1016/j.str.2010.10.006	journal	January 2011
Bayesian Energy Landscape Tilting: Towards Concordant Models of Molecular Ensembles Beauchamp, Kyle A.; Pande, Vijay S.; Das, Rhiju Biophysical Journal, Vol. 106, Issue 6 https://doi.org/10.1016/j.bpj.2014.02.009	journal	March 2014
Benchmark oxygen-oxygen pair-distribution function of ambient water from x-ray diffraction measurements with a wide Q -range Skinner, Lawrie B.; Huang, Congcong; Schlesinger, Daniel The Journal of Chemical Physics, Vol. 138, Issue 7 https://doi.org/10.1063/1.4790861	journal	February 2013
Cryo-EM Structures of the Actin:Tropomyosin Filament Reveal the Mechanism for the Transition from C- to M-State Sousa, Duncan R.; Stagg, Scott M.; Stroupe, M. Elizabeth Journal of Molecular Biology, Vol. 425, Issue 22 https://doi.org/10.1016/j.jmb.2013.08.020	journal	November 2013
Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method Barducci, Alessandro; Bussi, Giovanni; Parrinello, Michele Physical Review Letters, Vol. 100, Issue 2 https://doi.org/10.1103/PhysRevLett.100.020603	journal	January 2008
Efficient, Multiple-Range Random Walk Algorithm to Calculate the Density of States Wang, Fugao; Landau, D. P. Physical Review Letters, Vol. 86, Issue 10 https://doi.org/10.1103/PhysRevLett.86.2050	journal	March 2001
Molecular Dynamics in the Multicanonical Ensemble: Equivalence of Wang–Landau Sampling, Statistical Temperature Molecular Dynamics, and Metadynamics Junghans, Christoph; Perez, Danny; Vogel, Thomas Journal of Chemical Theory and Computation, Vol. 10, Issue 5 https://doi.org/10.1021/ct500077d	journal	April 2014
Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations Trebst, Simon; Huse, David A.; Troyer, Matthias Physical Review E, Vol. 70, Issue 4 https://doi.org/10.1103/PhysRevE.70.046701	journal	October 2004
Flux Tempered Metadynamics Singh, Sadanand; Chiu, Chi-cheng; de Pablo, Juan J. Journal of Statistical Physics, Vol. 145, Issue 4 https://doi.org/10.1007/s10955-011-0301-0	journal	September 2011
Accelerated weight histogram method for exploring free energy landscapes Lindahl, V.; Lidmar, J.; Hess, B. The Journal of Chemical Physics, Vol. 141, Issue 4 https://doi.org/10.1063/1.4890371	journal	July 2014
Exploring the free energy surfaces of clusters using reconnaissance metadynamics Tribello, Gareth A.; Cuny, Jérôme; Eshet, Hagai The Journal of Chemical Physics, Vol. 135, Issue 11 https://doi.org/10.1063/1.3628676	journal	September 2011
Assessing the Accuracy of Metadynamics ^† Laio, Alessandro; Rodriguez-Fortea, Antonio; Gervasio, Francesco Luigi The Journal of Physical Chemistry B, Vol. 109, Issue 14 https://doi.org/10.1021/jp045424k	journal	April 2005
Equilibrium Free Energies from Nonequilibrium Metadynamics Bussi, Giovanni; Laio, Alessandro; Parrinello, Michele Physical Review Letters, Vol. 96, Issue 9 https://doi.org/10.1103/PhysRevLett.96.090601	journal	March 2006
Transition-Tempered Metadynamics: Robust, Convergent Metadynamics via On-the-Fly Transition Barrier Estimation Dama, James F.; Rotskoff, Grant; Parrinello, Michele Journal of Chemical Theory and Computation, Vol. 10, Issue 9 https://doi.org/10.1021/ct500441q	journal	August 2014
A uniqueness theorem for fluid pair correlation functions Henderson, R. L. Physics Letters A, Vol. 49, Issue 3 https://doi.org/10.1016/0375-9601(74)90847-0	journal	September 1974
Metadynamics convergence law in a multidimensional system Crespo, Yanier; Marinelli, Fabrizio; Pietrucci, Fabio Physical Review E, Vol. 81, Issue 5 https://doi.org/10.1103/PhysRevE.81.055701	journal	May 2010
A boundary correction algorithm for metadynamics in multiple dimensions McGovern, Michael; de Pablo, Juan The Journal of Chemical Physics, Vol. 139, Issue 8 https://doi.org/10.1063/1.4818153	journal	August 2013
PLUMED: A portable plugin for free-energy calculations with molecular dynamics Bonomi, Massimiliano; Branduardi, Davide; Bussi, Giovanni Computer Physics Communications, Vol. 180, Issue 10 https://doi.org/10.1016/j.cpc.2009.05.011	journal	October 2009
Fast Parallel Algorithms for Short-Range Molecular Dynamics Plimpton, Steve Journal of Computational Physics, Vol. 117, Issue 1 https://doi.org/10.1006/jcph.1995.1039	journal	March 1995
Canonical dynamics: Equilibrium phase-space distributions Hoover, William G. Physical Review A, Vol. 31, Issue 3 https://doi.org/10.1103/PhysRevA.31.1695	journal	March 1985
Rapid estimation of elastic constants by molecular dynamics simulation under constant stress Shinoda, Wataru; Shiga, Motoyuki; Mikami, Masuhiro Physical Review B, Vol. 69, Issue 13 https://doi.org/10.1103/PhysRevB.69.134103	journal	April 2004
Molecular-dynamics study of a three-dimensional one-component model for distortive phase transitions Schneider, T.; Stoll, E. Physical Review B, Vol. 17, Issue 3 https://doi.org/10.1103/PhysRevB.17.1302	journal	February 1978
GROMACS: A message-passing parallel molecular dynamics implementation Berendsen, H. J. C.; van der Spoel, D.; van Drunen, R. Computer Physics Communications, Vol. 91, Issue 1-3 https://doi.org/10.1016/0010-4655(95)00042-E	journal	September 1995
All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins ^† MacKerell, A. D.; Bashford, D.; Bellott, M. The Journal of Physical Chemistry B, Vol. 102, Issue 18 https://doi.org/10.1021/jp973084f	journal	April 1998
Canonical sampling through velocity rescaling Bussi, Giovanni; Donadio, Davide; Parrinello, Michele The Journal of Chemical Physics, Vol. 126, Issue 1 https://doi.org/10.1063/1.2408420	journal	January 2007
A smooth particle mesh Ewald method Essmann, Ulrich; Perera, Lalith; Berkowitz, Max L. The Journal of Chemical Physics, Vol. 103, Issue 19 https://doi.org/10.1063/1.470117	journal	November 1995
LINCS: A linear constraint solver for molecular simulations Hess, Berk; Bekker, Henk; Berendsen, Herman J. C. Journal of Computational Chemistry, Vol. 18, Issue 12 https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H	journal	September 1997
Atomistic Modeling of the Electrode–Electrolyte Interface in Li-Ion Energy Storage Systems: Electrolyte Structuring Jorn, Ryan; Kumar, Revati; Abraham, Daniel P. The Journal of Physical Chemistry C, Vol. 117, Issue 8 https://doi.org/10.1021/jp3102282	journal	February 2013
Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model Ting, Daniel; Wang, Guoli; Shapovalov, Maxim PLoS Computational Biology, Vol. 6, Issue 4 https://doi.org/10.1371/journal.pcbi.1000763	journal	April 2010
A review of the features and analyses of the solid electrolyte interphase in Li-ion batteries Verma, Pallavi; Maire, Pascal; Novák, Petr Electrochimica Acta, Vol. 55, Issue 22, p. 6332-6341 https://doi.org/10.1016/j.electacta.2010.05.072	journal	September 2010
Interfacing electrolytes with electrodes in Li ion batteries Xu, Kang; von Cresce, Arthur Journal of Materials Chemistry, Vol. 21, Issue 27 https://doi.org/10.1039/c0jm04309e	journal	January 2011
The Solid Electrolyte Interphase – The Most Important and the Least Understood Solid Electrolyte in Rechargeable Li Batteries Winter, Martin Zeitschrift für Physikalische Chemie, Vol. 223, Issue 10-11 https://doi.org/10.1524/zpch.2009.6086	journal	December 2009
Quantum Chemistry and Molecular Dynamics Simulation Study of Dimethyl Carbonate: Ethylene Carbonate Electrolytes Doped with LiPF ₆ Borodin, Oleg; Smith, Grant D. The Journal of Physical Chemistry B, Vol. 113, Issue 6 https://doi.org/10.1021/jp809614h	journal	February 2009
Self-diffusion coefficient of dense fluids from the pair correlation function Bretonnet, Jean-Louis The Journal of Chemical Physics, Vol. 117, Issue 20 https://doi.org/10.1063/1.1516594	journal	November 2002
Pair Correlation Functions and the Self-Diffusion Coefficient of Lennard-Jones Liquid in the Modified Free Volume Theory of Diffusion Laghaei, Rozita; Eskandari Nasrabad, Afshin; Eu, Byung Chan The Journal of Physical Chemistry B, Vol. 109, Issue 45 https://doi.org/10.1021/jp050504p	journal	May 2005
Deriving effective mesoscale potentials from atomistic simulations: Mesoscale Potentials from Atomistic Simulations Reith, Dirk; Pütz, Mathias; Müller-Plathe, Florian Journal of Computational Chemistry, Vol. 24, Issue 13 https://doi.org/10.1002/jcc.10307	journal	August 2003
Quickstep: Fast and accurate density functional calculations using a mixed Gaussian and plane waves approach VandeVondele, Joost; Krack, Matthias; Mohamed, Fawzi Computer Physics Communications, Vol. 167, Issue 2 https://doi.org/10.1016/j.cpc.2004.12.014	journal	April 2005

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