4.8 Article

Conformational dynamics of a crystalline protein from microsecond-scale molecular dynamics simulations and diffuse X-ray scattering

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.1416744111

关键词

diffuse scattering; protein crystallography; molecular-dynamics simulation; protein dynamics; staphylococcal nuclease

资金

  1. US Department of Energy through the Laboratory-Directed Research and Development Program at Los Alamos National Laboratory [DE-AC52-06NA25396]
  2. NIH [GM095887, 1P01GM063210, OD009180, GM110580]
  3. National Science Foundation [STC-1231306]

向作者/读者索取更多资源

X-ray diffraction from protein crystals includes both sharply peaked Bragg reflections and diffuse intensity between the peaks. The information in Bragg scattering is limited to what is available in the mean electron density. The diffuse scattering arises from correlations in the electron density variations and therefore contains information about collective motions in proteins. Previous studies using molecular-dynamics (MD) simulations to model diffuse scattering have been hindered by insufficient sampling of the conformational ensemble. To overcome this issue, we have performed a 1.1-mu s MD simulation of crystalline staphylococcal nuclease, providing 100-fold more sampling than previous studies. This simulation enables reproducible calculations of the diffuse intensity and predicts functionally important motions, including transitions among at least eight metastable states with different active-site geometries. The total diffuse intensity calculated using the MD model is highly correlated with the experimental data. In particular, there is excellent agreement for the isotropic component of the diffuse intensity, and substantial but weaker agreement for the anisotropic component. Decomposition of the MD model into protein and solvent components indicates that protein-solvent interactions contribute substantially to the overall diffuse intensity. We conclude that diffuse scattering can be used to validate predictions from MD simulations and can provide information to improve MD models of protein motions.

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