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Related Concept Videos

X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

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X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal...
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The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
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Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
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AUSPEX: a graphical tool for X-ray diffraction data analysis.

Andrea Thorn1, James Parkhurst2, Paul Emsley3

  • 1Hamburg Centre for Ultrafast Imaging, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany.

Acta Crystallographica. Section D, Structural Biology
|September 7, 2017
PubMed
Summary
This summary is machine-generated.

AUSPEX is a new software tool for X-ray data analysis that helps researchers identify and fix problems in their experimental data. It can detect common issues like ice-ring artefacts, improving structural model accuracy.

Keywords:
AUSPEXX-ray diffractiondata analysisdata processingdata qualityice ringsmacromolecular crystallography

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Area of Science:

  • Crystallography
  • Structural Biology
  • Data Analysis

Background:

  • Experimental X-ray diffraction data analysis is crucial for determining structural models.
  • Identifying artefacts and errors in diffraction data is essential for accurate structure determination.
  • Modern pixel detectors generate large datasets where artefacts can be subtle.

Purpose of the Study:

  • To introduce AUSPEX, a novel software tool for analyzing experimental X-ray diffraction data.
  • To demonstrate AUSPEX's capability in identifying common data problems, such as ice-ring artefacts.
  • To highlight how AUSPEX can improve data quality and lead to better structural models.

Main Methods:

  • AUSPEX analyzes the distribution of observed X-ray diffraction intensities and their estimated uncertainties against resolution.
  • The software provides visual and automated methods for detecting artefacts.
  • It examines data quality issues arising from scaling and data conversion procedures.

Main Results:

  • AUSPEX effectively detects ice-ring artefacts in integrated X-ray diffraction data, which can hinder structure determination.
  • A significant percentage of data sets in the Protein Data Bank (PDB) appear to contain ice-ring artefacts.
  • The tool also identifies other experimental data problems, including those from scaling and data conversion.

Conclusions:

  • AUSPEX is a valuable tool for improving the quality of experimental X-ray diffraction data.
  • Early detection of artefacts and errors using AUSPEX can prevent downstream issues in structure determination.
  • The prevalence of ice-ring artefacts in deposited data underscores the need for robust data validation tools like AUSPEX.