Dataset Information

Identification of the point of diminishing returns in high-multiplicity data collection for sulfur SAD phasing.

ABSTRACT: High-quality high-multiplicity X-ray diffraction data were collected on five different crystals of thaumatin using a homogeneous-profile X-ray beam at E = 8?keV to investigate the counteracting effects of increased multiplicity and increased radiation damage on the quality of anomalous diffraction data collected on macromolecular crystals. By comparing sulfur substructures obtained from subsets of the data selected as a function of absorbed X-ray dose with sulfur positions in the respective refined reference structures, the doses at which the highest quality of anomalous differences could be obtained were identified for the five crystals. A statistic ?{?F}D, calculated as the width ? of the normalized distribution of a set {?F} of anomalous differences collected at a dose D, is suggested as a measure of anomalous data quality as a function of dose. An empirical rule is proposed to identify the dose at which the gains in data quality due to increased multiplicity are outbalanced by the losses due to decreases in signal-to-noise as a consequence of radiation damage. Identifying this point of diminishing returns allows the optimization of the choice of data collection parameters and the selection of data to be used in subsequent crystal structure determination steps.

SUBMITTER: Storm SL

PROVIDER: S-EPMC5182018 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of the point of diminishing returns in high-multiplicity data collection for sulfur SAD phasing.

Storm Selina L S SL Dall'Antonia Fabio F Bourenkov Gleb G Schneider Thomas R TR

Journal of synchrotron radiation 20170101 Pt 1

High-quality high-multiplicity X-ray diffraction data were collected on five different crystals of thaumatin using a homogeneous-profile X-ray beam at E = 8 keV to investigate the counteracting effects of increased multiplicity and increased radiation damage on the quality of anomalous diffraction data collected on macromolecular crystals. By comparing sulfur substructures obtained from subsets of the data selected as a function of absorbed X-ray dose with sulfur positions in the respective refi ...[more]

PMID: 28009543

Similar Datasets

Project description:A nonlinear least-squares method for refining a parametric expression describing the estimated errors of reflection intensities in serial crystallographic (SX) data is presented. This approach, which is similar to that used in the rotation method of crystallographic data collection at synchrotrons, propagates error estimates from photon-counting statistics to the merged data. Here, it is demonstrated that the application of this approach to SX data provides better SAD phasing ability, enabling the autobuilding of a protein structure that had previously failed to be built. Estimating the error in the merged reflection intensities requires the understanding and propagation of all of the sources of error arising from the measurements. One type of error, which is well understood, is the counting error introduced when the detector counts X-ray photons. Thus, if other types of random errors (such as readout noise) as well as uncertainties in systematic corrections (such as from X-ray attenuation) are completely understood, they can be propagated along with the counting error, as appropriate. In practice, most software packages propagate as much error as they know how to model and then include error-adjustment terms that scale the error estimates until they explain the variance among the measurements. If this is performed carefully, then during SAD phasing likelihood-based approaches can make optimal use of these error estimates, increasing the chance of a successful structure solution. In serial crystallography, SAD phasing has remained challenging, with the few examples of de novo protein structure solution each requiring many thousands of diffraction patterns. Here, the effects of different methods of treating the error estimates are estimated and it is shown that using a parametric approach that includes terms proportional to the known experimental uncertainty, the reflection intensity and the squared reflection intensity to improve the error estimates can allow SAD phasing even from weak zinc anomalous signal.

Dataset Information

Identification of the point of diminishing returns in high-multiplicity data collection for sulfur SAD phasing.

Publications

Identification of the point of diminishing returns in high-multiplicity data collection for sulfur SAD phasing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets