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The PDB_REDO server for macromolecular structure model optimization - PubMed

  • ️Wed Jan 01 2014

The PDB_REDO server for macromolecular structure model optimization

Robbie P Joosten et al. IUCrJ. 2014.

Abstract

The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB). The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011 ▶), Structure, 19, 1395-1412]. The PDB_REDO procedure aims for 'constructive validation', aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB_REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallo-graphers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB_REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB.

Keywords: PDB_REDO; model optimization; validation.

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Figures

Figure 1
Figure 1

Example output of the PDB_REDO web server. (a) The table of global structure model quality indicators for the starting model and the final PDB_REDO model. Significant improvements are marked in green and deteriorations in red. See the main text for a description of the significance levels. The blue question marks are hyperlinks to the PDB_REDO FAQ. (b) Box-and-whisker plots of global model quality indicators. The plots represent quality scores of at least 1000 structure models (from the PDB or their PDB_REDO data bank counterparts) that have a resolution close to that of the user’s model. The whiskers extend to 1.5 times the inter-quartile range. The quality of the starting model is indicated as a blue line and that of the final model as an orange line. (c) Changes in real-space correlation coefficient per residue (for the N-terminal part of a study case). Significant improvements are coloured green and deteriorations red, while grey denotes no significant change and white denotes undefined significance; the dotted line denotes the average change across the whole protein. This plot also demonstrates that the significance of a change depends on the magnitude but also on the size of the residue and the resolution of the diffraction data. (d) A Coot (Emsley et al., 2010 ▶) window with a button list that highlights the structural changes made by the PDB_REDO pipeline.

Figure 2
Figure 2

The personal, password-protected, workspace on the PDB_REDO web server from which jobs can be submitted, inspected and deleted.

Figure 3
Figure 3

Comparison of model quality scores of starting models and final PDB_REDO models as histograms of score change. The values on the x axis mark the upper limit of each bin. Improvements are marked in green, deteriorations in red and neutral changes in yellow. (a) R free as calculated by REFMAC (Murshudov et al., 2011 ▶). (b) Ramachandran plot Z-score from WHAT_CHECK (Hooft et al., 1996 ▶). (c) Rotamer normality Z-score from WHAT_CHECK. (d) Fine (second-generation) packing Z-score from WHAT_CHECK. (e) Weighted bump severity score (see equation 4).

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