Chapter 21.1 Validation of protein crystal structures

Since the process of building and refining a model of a biomacromolecule based on crystallographic data is subjective, quality-control techniques are required to assess the validity of such models. During the 1990s, much experience was gained; the methods used and some of the lessons learned are reviewed here. In addition, an extensive compendium of quality criteria and quality-control methods that are or have been used to validate models of biomacromolecules has been compiled. The emphasis in this compendium is on the validation of protein crystal structures.

Keywords: accuracy; atomic displacement parameters (temperature factors); Calpha-only model; coordinate errors; data completeness; data resolution; difference density quality; errors; merging R factors; noncrystallographic symmetry; outliers; quality indicators; real-space fit; signal strength and structure validation; solvent; structure validation; temperature factors (atomic displacement parameters); unit-cell parameters