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Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models

Pär BjelkmarCenter for Biomembrane Research, Department of Biochemistry & Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, and Molecular Modeling Group, Swiss Institute of Bioinformatics, CH-1015 Lausanne, SwitzerlandPer LarssonCenter for Biomembrane Research, Department of Biochemistry & Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, and Molecular Modeling Group, Swiss Institute of Bioinformatics, CH-1015 Lausanne, SwitzerlandMichel A. CuendetCenter for Biomembrane Research, Department of Biochemistry & Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, and Molecular Modeling Group, Swiss Institute of Bioinformatics, CH-1015 Lausanne, SwitzerlandBerk HessCenter for Biomembrane Research, Department of Biochemistry & Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, and Molecular Modeling Group, Swiss Institute of Bioinformatics, CH-1015 Lausanne, SwitzerlandErik LindahlCenter for Biomembrane Research, Department of Biochemistry & Biophysics, Stockholm University, SE-106 91 Stockholm, Sweden, and Molecular Modeling Group, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland

2010en

ABI

Annotatsiya

CHARMM27 is a widespread and popular force field for biomolecular simulation, and several recent algorithms such as implicit solvent models have been developed specifically for it. We have here implemented the CHARMM force field and all necessary extended functional forms in the GROMACS molecular simulation package, to make CHARMM-specific features available and to test them in combination with techniques for extended time steps, to make all major force fields available for comparison studies in GROMACS, and to test various solvent model optimizations, in particular the effect of Lennard-Jones interactions on hydrogens. The implementation has full support both for CHARMM-specific features such as multiple potentials over the same dihedral angle and the grid-based energy correction map on the ϕ, ψ protein backbone dihedrals, as well as all GROMACS features such as virtual hydrogen interaction sites that enable 5 fs time steps. The medium-to-long time effects of both the correction maps and virtual sites have been tested by performing a series of 100 ns simulations using different models for water representation, including comparisons between CHARMM and traditional TIP3P. Including the correction maps improves sampling of near native-state conformations in our systems, and to some extent it is even able to refine distorted protein conformations. Finally, we show that this accuracy is largely maintained with a new implicit solvent implementation that works with virtual interaction sites, which enables performance in excess of 250 ns/day for a 900-atom protein on a quad-core desktop computer.

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Identifikatorlar

DOI: 10.1021/ct900549r

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