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Title: Continuous mutual improvement of macromolecular structure models in the PDB and of X-ray crystallographic software: The dual role of deposited experimental data

Journal Article · · Acta Crystallographica. Section D: Biological Crystallography (Online)
 [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Global Phasing Ltd., Cambridge (England)

Accurate crystal structures of macromolecules are of high importance in the biological and biomedical fields. Models of crystal structures in the Protein Data Bank (PDB) are in general of very high quality as deposited. However, methods for obtaining the best model of a macromolecular structure from a given set of experimental X-ray data continue to progress at a rapid pace, making it possible to improve most PDB entries after their deposition by re-analyzing the original deposited data with more recent software. This possibility represents a very significant departure from the situation that prevailed when the PDB was created, when it was envisioned as a cumulative repository of static contents. A radical paradigm shift for the PDB is therefore proposed, away from the static archive model towards a much more dynamic body of continuously improving results in symbiosis with continuously improving methods and software. These simultaneous improvements in methods and final results are made possible by the current deposition of processed crystallographic data (structure-factor amplitudes) and will be supported further by the deposition of raw data (diffraction images). It is argued that it is both desirable and feasible to carry out small-scale and large-scale efforts to make this paradigm shift a reality. Small-scale efforts would focus on optimizing structures that are of interest to specific investigators. Large-scale efforts would undertake a systematic re-optimization of all of the structures in the PDB, or alternatively the redetermination of groups of structures that are either related to or focused on specific questions. All of the resulting structures should be made generally available, along with the precursor entries, with various views of the structures being made available depending on the types of questions that users are interested in answering.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1212454
Journal Information:
Acta Crystallographica. Section D: Biological Crystallography (Online), Vol. 70, Issue 10; ISSN 1399-0047
Publisher:
International Union of CrystallographyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 29 works
Citation information provided by
Web of Science

Cited By (8)

Synchrotron Big Data Science journal September 2018
The Integrated Resource for Reproducibility in Macromolecular Crystallography: Experiences of the first four years journal November 2019
Homology-based loop modelling yields more complete crystallographic protein structures journal May 2018
The science is in the data journal October 2017
Findable Accessible Interoperable Re-usable (FAIR) diffraction data are coming to protein crystallography journal April 2019
Naked Metal Cations Swimming in Protein Crystals journal November 2019
Findable Accessible Interoperable Re-usable (FAIR) diffraction data are coming to protein crystallography journal April 2019
Findable Accessible Interoperable Re-usable (FAIR) diffraction data are coming to protein crystallography journal April 2019

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