Nathan Schmid

Definition and testing of the GROMOS force-field versions 54A7 and 54B7.

New parameter sets of the GROMOS biomolecular force field, 54A7 and 54B7, are introduced. These parameter sets summarise some previously published force field modifications: The 53A6 helical propensities are corrected through new φ/ψ torsional angle terms and a modification of the N–H, C=O repulsion, a new atom type for a charged −CH3 in the choline moiety is added, the Na+ and Cl− ions are modified to reproduce the free energy of hydration, and additional improper torsional angle types for free energy calculations involving a chirality change are introduced. The new helical propensity modification is tested using the benchmark proteins hen egg-white lysozyme, fox1 RNA binding domain, chorismate mutase and the GCN4-p1 peptide. The stability of the proteins is improved in comparison with the 53A6 force field, and good agreement with a range of primary experimental data is obtained.

Architecture, implementation and parallelisation of the GROMOS software for biomolecular simulation☆

Abstract In this work the design of the latest version of the GROMOS software for biomolecular simulation, GROMOS11 is discussed. Detailed organisation and class descriptions of the MD++ simulation program and the GROMOS++ analysis package are given. It is shown how the code was documented, how it can be easily modified and extended, how debugging of it is carried out. Additional efficiency and parallelisation concepts are presented and benchmarked.

GROMOS++ Software for the Analysis of Biomolecular Simulation Trajectories

GROMOS++ is a set of C++ programs for pre- and postprocessing of molecular dynamics simulation trajectories and as such is part of the GROningen MOlecular Simulation software for (bio)molecular simulation. It contains more than 70 programs that can be used to prepare data for the production of molecular simulation trajectories and to analyze these. These programs are reviewed and the various structural, dynamic, and thermodynamic quantities that can be analyzed using time series, correlation functions, and distributions are described together with technical aspects of their implementation in GROMOS. A few examples of the use of GROMOS++ for the analysis of MD trajectories are given. A full list of all GROMOS++ programs, together with an indication of their capabilities, is given in the Appendix .

New functionalities in the GROMOS biomolecular simulation software

Since the most recent description of the functionalities of the GROMOS software for biomolecular simulation in 2005 many new functions have been implemented. In this article, the new functionalities that involve modified forces in a molecular dynamics (MD) simulation are described: the treatment of electronic polarizability, an implicit surface area and internal volume solvation term to calculate interatomic forces, functions for the GROMOS coarse‐grained supramolecular force field, a multiplicative switching function for nonbonded interactions, adiabatic decoupling of a number of degrees of freedom with temperature or force scaling to enhance sampling, and nonequilibrium MD to calculate the dielectric permittivity or viscosity. Examples that illustrate the use of these functionalities are given.

Biomolecular structure refinement using the GROMOS simulation software

For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, 3J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

A GPU solvent–solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software

During the past few years, graphics processing units (GPUs) have become extremely popular in the high performance computing community. In this study, we present an implementation of an acceleration engine for the solvent–solvent interaction evaluation of molecular dynamics simulations. By careful optimization of the algorithm speed‐ups up to a factor of 54 (single‐precision GPU vs. double‐precision CPU) could be achieved. The accuracy of the single‐precision GPU implementation is carefully investigated and does not influence structural, thermodynamic, and dynamic quantities. Therefore, the implementation enables users of the GROMOS software for biomolecular simulation to run the solvent–solvent interaction evaluation on a GPU, and thus, to speed‐up their simulations by a factor 6–9.

The effect of using a polarizable solvent model upon the folding equilibrium of different β-peptides

Folding and unfolding of β-peptides has been studied extensively by molecular dynamics (MD) simulation in the past decade. In these simulations, a non-polarizable model for the solvent (mostly methanol) was used. This work has investigated the effect of using a polarizable methanol solvent model upon the folding equilibrium of β-peptides. Thirteen MD simulations covering a total simulation length of 1.25 µs for three differently folding β-peptides were analyzed. The agreement with experimental data was slightly improved by applying the polarizable solvent. In the polarizable solvent, helical structures, which have a large dipole moment, are stabilized, while no obvious effect was detected in the simulations of peptides that have a hairpin structure as the dominant fold. The introduction of electronic polarizability into the solvent model appears of importance to a proper description of folding equilibria if these are determined by competing solute conformations that have different dipole moments.

Time-averaged order parameter restraints in molecular dynamics simulations

Abstract A method is described that allows experimental

Disulfide bond shuffling in bovine alpha-lactalbumin: MD simulation confirms experiment.

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