Dataset Information

Geometry and Excitation Energy Fluctuations of NMA in Aqueous Solution with CHARMM, AMBER, OPLS, and GROMOS Force Fields: Implications for Protein Ultraviolet Spectra Simulation.

ABSTRACT: Molecular dynamics (MD) simulations are performed for N-methylamide (NMA) in water at 300 K with different force fields. Compared to the three all-atom force fields (CHARMM22, AMBER03, and OPLS-AA), the united-atom force field (GROMOS96) predicts a broader distribution of the peptide OCNH dehedral angle. A map constructed by fitting the npi* and pipi* transition energies as quadratic functions of the NMA geometric variables is used to simulate the excitation energy fluctuations. GROMOS96 predicts blue-shifted npi* and pipi* energies and stronger fluctuations compared to the other three force fields, which indicates that different force fields may predict different spectral lineshapes for proteins.

SUBMITTER: Li Z

PROVIDER: S-EPMC2344158 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature

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Geometry and Excitation Energy Fluctuations of NMA in Aqueous Solution with CHARMM, AMBER, OPLS, and GROMOS Force Fields: Implications for Protein Ultraviolet Spectra Simulation.

Li Zhenyu Z Yu Haibo H Zhuang Wei W Mukamel Shaul S

Chemical physics letters 20080201 1-3

Molecular dynamics (MD) simulations are performed for N-methylamide (NMA) in water at 300 K with different force fields. Compared to the three all-atom force fields (CHARMM22, AMBER03, and OPLS-AA), the united-atom force field (GROMOS96) predicts a broader distribution of the peptide OCNH dehedral angle. A map constructed by fitting the npi* and pipi* transition energies as quadratic functions of the NMA geometric variables is used to simulate the excitation energy fluctuations. GROMOS96 predict ...[more]

PMID: 18438457

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Project description:All-atom molecular dynamics simulations with stratified alchemical free energy calculations were used to predict the octanol-water partition coefficient [Formula: see text] of eleven small molecules as part of the SAMPL6-[Formula: see text] blind prediction challenge using four different force field parametrizations: standard OPLS-AA with transferable charges, OPLS-AA with non-transferable CM1A charges, AMBER/GAFF, and CHARMM/CGenFF. Octanol parameters for OPLS-AA, GAFF and CHARMM were validated by comparing the density as a function of temperature, the chemical potential, and the hydration free energy to experimental values. The partition coefficients were calculated from the solvation free energy for the compounds in water and pure ("dry") octanol or "wet" octanol with 27 mol% water dissolved. Absolute solvation free energies were computed by thermodynamic integration (TI) and the multistate Bennett acceptance ratio with uncorrelated samples from data generated by an established protocol using 5-ns windowed alchemical free energy perturbation (FEP) calculations with the Gromacs molecular dynamics package. Equilibration of sets of FEP simulations was quantified by a new measure of convergence based on the analysis of forward and time-reversed trajectories. The accuracy of the [Formula: see text] predictions was assessed by descriptive statistical measures such as the root mean square error (RMSE) of the data set compared to the experimental values. Discarding the first 1 ns of each 5-ns window as an equilibration phase had a large effect on the GAFF data, where it improved the RMSE by up to 0.8 log units, while the effect for other data sets was smaller or marginally worsened the agreement. Overall, CGenFF gave the best prediction with RMSE 1.2 log units, although for only eight molecules because the current CGenFF workflow for Gromacs does not generate files for certain halogen-containing compounds. Over all eleven compounds, GAFF gave an RMSE of 1.5. The effect of using a mixed water/octanol solvent slightly decreased the accuracy for CGenFF and GAFF and slightly increased it for OPLS-AA. The GAFF and OPLS-AA results displayed a systematic error where molecules were too hydrophobic whereas CGenFF appeared to be more balanced, at least on this small data set.

Dataset Information

Geometry and Excitation Energy Fluctuations of NMA in Aqueous Solution with CHARMM, AMBER, OPLS, and GROMOS Force Fields: Implications for Protein Ultraviolet Spectra Simulation.

Publications

Geometry and Excitation Energy Fluctuations of NMA in Aqueous Solution with CHARMM, AMBER, OPLS, and GROMOS Force Fields: Implications for Protein Ultraviolet Spectra Simulation.

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