Crystallographic Data and Model Quality.

This article gives a consistent classification of sources of random and systematic errors in crystallographic data, and their influence on the averaged dataset obtained from a diffraction experiment. It discusses the relation between precision and accuracy and the crystallographic indicators used to estimate them, as well as topics like completeness and high-resolution cutoff. These concepts are applied in the context of presenting good practices for data processing with a widely used package, XDS. Recommendations are given for how to minimize the impact of several typical problems, like ice rings and shaded areas. Then, procedures for optimizing the processing parameters are explained. Finally, a simple graphical expression of some basic relations between data error and model error is suggested.

[1]  K. Diederichs.  Simulation of X-ray frames from macromolecular crystals using a ray-tracing approach. , 2009, Acta crystallographica. Section D, Biological crystallography.

[2]  Lirong Chen,et al.  A multi-dataset data-collection strategy produces better diffraction data , 2011, Acta crystallographica. Section A, Foundations of crystallography.

[3]  A. N. Popov,et al.  Optimization of data collection taking radiation damage into account , 2010, Acta crystallographica. Section D, Biological crystallography.

[4]  P. Evans,et al.  Scaling and assessment of data quality. , 2006, Acta crystallographica. Section D, Biological crystallography.

[5]  Kay Diederichs,et al.  Some aspects of quantitative analysis and correction of radiation damage. , 2006, Acta crystallographica. Section D, Biological crystallography.

[6]  George M Sheldrick,et al.  Substructure solution with SHELXD. , 2002, Acta crystallographica. Section D, Biological crystallography.

[7]  R. Ravelli,et al.  The 'fingerprint' that X-rays can leave on structures. , 2000, Structure.

[8]  Kay Diederichs.  Quantifying instrument errors in macromolecular X-ray data sets. , 2010, Acta crystallographica. Section D, Biological crystallography.

[9]  G Bricogne,et al.  Phasing in the presence of severe site-specific radiation damage through dose-dependent modelling of heavy atoms. , 2004, Acta crystallographica. Section D, Biological crystallography.

[10]  Manfred S. Weiss,et al.  Global indicators of X-ray data quality , 2001 .

[11]  A.J.C. Wilson,et al.  Largest likely values for the reliability index , 1950 .

[12]  Philip R. Evans,et al.  An introduction to data reduction: space-group determination, scaling and intensity statistics , 2011, Acta crystallographica. Section D, Biological crystallography.

[13]  R. Crowther,et al.  A computer-linked cathode-ray tube microdensitometer for x-ray crystallography. , 1968, Journal of scientific instruments.

[14]  W. Burmeister,et al.  Structural changes in a cryo-cooled protein crystal owing to radiation damage. , 2000, Acta crystallographica. Section D, Biological crystallography.

[15]  K. Diederichs,et al.  Better models by discarding data? , 2013, Acta crystallographica. Section D, Biological crystallography.

[16]  Sean McSweeney,et al.  Zero-dose extrapolation as part of macromolecular synchrotron data reduction. , 2003, Acta crystallographica. Section D, Biological crystallography.

[17]  Wladek Minor,et al.  Measurement errors and their consequences in protein crystallography. , 2003, Acta crystallographica. Section D, Biological crystallography.

[18]  P. Andrew Karplus,et al.  Linking Crystallographic Model and Data Quality , 2012, Science.

[19]  Anton Barty,et al.  Crystallographic data processing for free-electron laser sources , 2013, Acta crystallographica. Section D, Biological crystallography.

[20]  M. Jaskólski,et al.  Protein crystallography for non‐crystallographers, or how to get the best (but not more) from published macromolecular structures , 2008, The FEBS journal.

[21]  Frank von Delft,et al.  Assessment of radiation damage behaviour in a large collection of empirically optimized datasets highlights the importance of unmeasured complicating effects , 2011, Journal of synchrotron radiation.

[22]  Update on the tutorial for learning and teaching macromolecular crystallography , 2010 .

[23]  Philip R. Evans,et al.  How good are my data and what is the resolution? , 2013, Acta crystallographica. Section D, Biological crystallography.

[24]  P. Andrew Karplus,et al.  Improved R-factors for diffraction data analysis in macromolecular crystallography , 1997, Nature Structural Biology.

[25]  Wolfgang Kabsch,et al.  Integration, scaling, space-group assignment and post-refinement , 2010, Acta crystallographica. Section D, Biological crystallography.