Re-refinement from deposited X-ray data can deliver improved models for most PDB entries.
The deposition of X-ray data along with the customary structural models defining PDB entries makes it possible to apply large-scale re-refinement protocols to these entries, thus giving users the benefit of improvements in X-ray methods that have occurred since the structure was deposited. Automated gradient refinement is an effective method to achieve this goal, but real-space intervention is most often required in order to adequately address problems detected by structure-validation software. In order to improve the existing protocol, automated re-refinement was combined with structure validation and difference-density peak analysis to produce a catalogue of problems in PDB entries that are amenable to automatic correction. It is shown that re-refinement can be effective in producing improvements, which are often associated with the systematic use of the TLS parameterization of B factors, even for relatively new and high-resolution PDB entries, while the accompanying manual or semi-manual map analysis and fitting steps show good prospects for eventual automation. It is proposed that the potential for simultaneous improvements in methods and in re-refinement results be further encouraged by broadening the scope of depositions to include refinement metadata and ultimately primary rather than reduced X-ray data.
Joosten
Robbie P
RP
CMBI, NCMLS, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.
Womack
Thomas
T
Vriend
Gert
G
Bricogne
Gérard
G
D019295:Computational Biology / Q000379:methods; D018360:Crystallography, X-Ray / Q000379:methods*; D030562:Databases, Protein; D016247:Information Storage and Retrieval; D012984:Software