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Molecular dynamics simulations of an enzyme surrounded by vacuum, water, or a hydrophobic solvent.

ABSTRACT: We report on molecular dynamics simulations of a medium-sized protein, a lipase from Rhizomucor miehei, in vacuum, in water, and in a nonpolar solvent, methyl hexanoate. Depending on force field and solvent, the molecular dynamics structures obtained as averages over 150 ps had root-mean-square deviations in the range of 1.9 to 3.6 A from the crystal structure. The largest differences between the structures were in hydrogen bonding and exposed surface areas of the protein. The surface area increased in both solvents and became smaller in vacuum. The change of surface exposure varied greatly between different residues and occurred in accordance with the hydrophobicity of the residue and the nature of the solvent. The fluctuations of the atoms were largest in the external loops and agreed well with crystallographic temperature factors. Root-mean-square fluctuations were significantly smaller in the nonpolar solvents than they were in water, which is in accordance with the notion that proteins become more rigid in nonpolar solvents. In methyl hexanoate a partial opening of the lid covering the active site occurred, letting a methyl hexanoate molecule approach the active site.

SUBMITTER: Norin M

PROVIDER: S-EPMC1225398 | biostudies-other | 1994 Aug

REPOSITORIES: biostudies-other

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Molecular dynamics simulations of an enzyme surrounded by vacuum, water, or a hydrophobic solvent.

Norin M M Haeffner F F Hult K K Edholm O O

Biophysical journal 19940801 2

We report on molecular dynamics simulations of a medium-sized protein, a lipase from Rhizomucor miehei, in vacuum, in water, and in a nonpolar solvent, methyl hexanoate. Depending on force field and solvent, the molecular dynamics structures obtained as averages over 150 ps had root-mean-square deviations in the range of 1.9 to 3.6 A from the crystal structure. The largest differences between the structures were in hydrogen bonding and exposed surface areas of the protein. The surface area incre ...[more]

PMID: 7948673

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Project description:Adequate sampling of conformation space remains challenging in atomistic simulations, especially if the solvent is treated explicitly. Implicit-solvent simulations can speed up conformational sampling significantly. We compare the speed of conformational sampling between two commonly used methods of each class: the explicit-solvent particle mesh Ewald (PME) with TIP3P water model and a popular generalized Born (GB) implicit-solvent model, as implemented in the AMBER package. We systematically investigate small (dihedral angle flips in a protein), large (nucleosome tail collapse and DNA unwrapping), and mixed (folding of a miniprotein) conformational changes, with nominal simulation times ranging from nanoseconds to microseconds depending on system size. The speedups in conformational sampling for GB relative to PME simulations, are highly system- and problem-dependent. Where the simulation temperatures for PME and GB are the same, the corresponding speedups are approximately onefold (small conformational changes), between ∼1- and ∼100-fold (large changes), and approximately sevenfold (mixed case). The effects of temperature on speedup and free-energy landscapes, which may differ substantially between the solvent models, are discussed in detail for the case of miniprotein folding. In addition to speeding up conformational sampling, due to algorithmic differences, the implicit solvent model can be computationally faster for small systems or slower for large systems, depending on the number of solute and solvent atoms. For the conformational changes considered here, the combined speedups are approximately twofold, ∼1- to 60-fold, and ∼50-fold, respectively, in the low solvent viscosity regime afforded by the implicit solvent. For all the systems studied, 1) conformational sampling speedup increases as Langevin collision frequency (effective viscosity) decreases; and 2) conformational sampling speedup is mainly due to reduction in solvent viscosity rather than possible differences in free-energy landscapes between the solvent models.

Dataset Information

Molecular dynamics simulations of an enzyme surrounded by vacuum, water, or a hydrophobic solvent.

Publications

Molecular dynamics simulations of an enzyme surrounded by vacuum, water, or a hydrophobic solvent.

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