Related Experiment Videos
Intensity statistics in twinned crystals with examples from the PDB
Andrey A Lebedev1, Alexei A Vagin, Garib N Murshudov
1Structural Biology Laboratory, Department of Chemistry, University of York, Heslington, York YO10 5YW, England. lebedev@ysbl.york.ac.uk
Acta Crystallographica. Section D, Biological Crystallography
|December 22, 2005
Summary
This study analyzed Protein Data Bank entries to identify crystal twinning, often overlooked during structure solution. Incorporating twinning detection early is crucial for accurate crystallographic analysis.
Area of Science:
- Crystallography
- Structural Biology
- Data Analysis
Background:
- Crystal twinning, where multiple symmetry-related crystal lattices are present, can complicate crystallographic structure determination.
- Existing methods for detecting twinning may not be sufficient, especially when rotational pseudosymmetry is present.
Purpose of the Study:
- To analyze Protein Data Bank entries for instances of crystal twinning.
- To investigate the relationship between twinning and rotational pseudosymmetry.
- To propose improvements for twinning detection in crystallographic workflows.
Main Methods:
- Analysis of Protein Data Bank entries (as of February 2004) with available model and X-ray data.
- Utilized simple statistical measures, such as the R factor between potential twin-related reflections, for initial identification.
- Performed manual analysis of crystal models to understand the association with pseudosymmetry.
Main Results:
- Identified numerous cases of crystal twinning within the analyzed dataset.
- Observed that twinning was frequently ignored during structure solution and refinement processes.
- Found a common association between crystal twinning and rotational pseudosymmetry parallel to the twinning operator.
Conclusions:
- The coexistence of twinning and rotational pseudosymmetry complicates current detection methods.
- A dedicated twinning detection step is recommended throughout all stages of structure analysis, from data acquisition to refinement and validation.