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

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.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Lab. (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, Journal Name: Journal of Chemical Theory and Computation Journal Issue: 6 Vol. 11; ISSN 1549-9618

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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