Improved Fitting of Solution X-ray Scattering Data to Macromolecular Structures and Structural Ensembles by Explicit Water Modeling

A new procedure, AXES, is introduced for fitting small-angle X-ray scattering (SAXS) data to macromolecular structures and ensembles of structures. By using explicit water models to account for the effect of solvent, and by restricting the adjustable fitting parameters to those that dominate experim...

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Bibliographic Details
Published inJournal of the American Chemical Society Vol. 132; no. 44; pp. 15484 - 15486
Main Authors Grishaev, Alexander, Guo, Liang, Irving, Thomas, Bax, Ad
Format Journal Article
LanguageEnglish
Published United States American Chemical Society 10.11.2010
Subjects
Adjustable
BASIC BIOLOGICAL SCIENCES
Communication
Density
Detectors
Fittings
GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
HYDRATION
Macromolecular Substances - chemistry
Mathematical models
Models, Molecular
PROTEIN STRUCTURE
PROTEINS
RESOLUTION
SAXS
SCATTERING
Scattering, Small Angle
SIMULATION
WATER
Water - chemistry
X-Rays
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Summary:A new procedure, AXES, is introduced for fitting small-angle X-ray scattering (SAXS) data to macromolecular structures and ensembles of structures. By using explicit water models to account for the effect of solvent, and by restricting the adjustable fitting parameters to those that dominate experimental uncertainties, including sample/buffer rescaling, detector dark current, and, within a narrow range, hydration layer density, superior fits between experimental high resolution structures and SAXS data are obtained. AXES results are found to be more discriminating than standard Crysol fitting of SAXS data when evaluating poorly or incorrectly modeled protein structures. AXES results for ensembles of structures previously generated for ubiquitin show improved fits over fitting of the individual members of these ensembles, indicating these ensembles capture the dynamic behavior of proteins in solution.
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USDOE
Illinois Institute of Technology.
National Institutes of Health.
ISSN:0002-7863
1520-5126
DOI:10.1021/ja106173n