Dataset Information

Force field independent metal parameters using a nonbonded dummy model.

ABSTRACT: The cationic dummy atom approach provides a powerful nonbonded description for a range of alkaline-earth and transition-metal centers, capturing both structural and electrostatic effects. In this work we refine existing literature parameters for octahedrally coordinated Mn(2+), Zn(2+), Mg(2+), and Ca(2+), as well as providing new parameters for Ni(2+), Co(2+), and Fe(2+). In all the cases, we are able to reproduce both M(2+)-O distances and experimental solvation free energies, which has not been achieved to date for transition metals using any other model. The parameters have also been tested using two different water models and show consistent performance. Therefore, our parameters are easily transferable to any force field that describes nonbonded interactions using Coulomb and Lennard-Jones potentials. Finally, we demonstrate the stability of our parameters in both the human and Escherichia coli variants of the enzyme glyoxalase I as showcase systems, as both enzymes are active with a range of transition metals. The parameters presented in this work provide a valuable resource for the molecular simulation community, as they extend the range of metal ions that can be studied using classical approaches, while also providing a starting point for subsequent parametrization of new metal centers.

SUBMITTER: Duarte F

PROVIDER: S-EPMC4180081 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Force field independent metal parameters using a nonbonded dummy model.

Duarte Fernanda F Bauer Paul P Barrozo Alexandre A Amrein Beat Anton BA Purg Miha M Aqvist Johan J Kamerlin Shina Caroline Lynn SC

The journal of physical chemistry. B 20140415 16

The cationic dummy atom approach provides a powerful nonbonded description for a range of alkaline-earth and transition-metal centers, capturing both structural and electrostatic effects. In this work we refine existing literature parameters for octahedrally coordinated Mn(2+), Zn(2+), Mg(2+), and Ca(2+), as well as providing new parameters for Ni(2+), Co(2+), and Fe(2+). In all the cases, we are able to reproduce both M(2+)-O distances and experimental solvation free energies, which has not bee ...[more]

PMID: 24670003

Similar Datasets

Project description:There is a small, but growing, body of literature describing the use of osmotic coefficient measurements to validate and reparametrize simulation force fields. Here we have investigated the ability of five very commonly used force field and water model combinations to reproduce the osmotic coefficients of seven neutral amino acids and five small molecules. The force fields tested include AMBER ff99SB-ILDN, CHARMM36, GROMOS54a7, and OPLS-AA, with the first of these tested in conjunction with the TIP3P and TIP4P-Ew water models. In general, for both the amino acids and the small molecules, the tested force fields produce computed osmotic coefficients that are lower than experiment; this is indicative of excessively favorable solute-solute interactions. The sole exception to this general trend is provided by GROMOS54a7 when applied to amino acids: in this case, the computed osmotic coefficients are consistently too high. Importantly, we show that all of the force fields tested can be made to accurately reproduce the experimental osmotic coefficients of the amino acids when minor modifications-some previously reported by others and some that are new to this study-are made to the van der Waals interactions of the charged terminal groups. Special care is required, however, when simulating Proline with a number of the force fields, and a hydroxyl-group specific modification is required in order to correct Serine and Threonine when simulated with AMBER ff99SB-ILDN. Interestingly, an alternative parametrization of the van der Waals interactions in the latter force field, proposed by the Nerenberg and Head-Gordon groups, is shown to immediately produce osmotic coefficients that are in excellent agreement with experiment. Overall, this study reinforces the idea that osmotic coefficient measurements can be used to identify general shortcomings in commonly used force fields' descriptions of solute-solute interactions and further demonstrates that modifications to van der Waals parameters provide a simple route to optimizing agreement with experiment.

Project description:Accurate representations of van der Waals dispersion-repulsion interactions play an important role in high-quality molecular dynamics simulations. Training the force field parameters used in the Lennard Jones (LJ) potential typically used to represent these interactions is challenging, generally requiring adjustment based on simulations of macroscopic physical properties. The large computational expense of these simulations, especially when many parameters must be trained simultaneously, limits the size of training data set and number of optimization steps that can be taken, often requiring modelers to perform optimizations within a local parameter region. To allow for more global LJ parameter optimization against large training sets, we introduce a multi-fidelity optimization technique which uses Gaussian process surrogate modeling to build inexpensive models of physical properties as a function of LJ parameters. This approach allows for fast evaluation of approximate objective functions, greatly accelerating searches over parameter space and enabling the use of optimization algorithms capable of searching more globally. In this study, we use an iterative framework which performs global optimization with differential evolution at the surrogate level, followed by validation at the simulation level and surrogate refinement. Using this technique on two previously studied training sets, containing up to 195 physical property targets, we refit a subset of the LJ parameters for the OpenFF 1.0.0 (Parsley) force field. We demonstrate that this multi-fidelity technique can find improved parameter sets compared to a purely simulation-based optimization by searching more broadly and escaping local minima. Additionally, this technique often finds significantly different parameter minima that have comparably accurate performance. In most cases, these parameter sets are transferable to other similar molecules in a test set. Our multi-fidelity technique provides a platform for rapid, more global optimization of molecular models against physical properties, as well as a number of opportunities for further refinement of the technique.

Dataset Information

Force field independent metal parameters using a nonbonded dummy model.

Publications

Force field independent metal parameters using a nonbonded dummy model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets