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      Toward the estimation of the absolute quality of individual protein structure models

      research-article
      1 , 2 , 1 , 2 , 1 , 2 , *
      Bioinformatics
      Oxford University Press

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          Abstract

          Motivation: Quality assessment of protein structures is an important part of experimental structure validation and plays a crucial role in protein structure prediction, where the predicted models may contain substantial errors. Most current scoring functions are primarily designed to rank alternative models of the same sequence supporting model selection, whereas the prediction of the absolute quality of an individual protein model has received little attention in the field. However, reliable absolute quality estimates are crucial to assess the suitability of a model for specific biomedical applications.

          Results: In this work, we present a new absolute measure for the quality of protein models, which provides an estimate of the ‘degree of nativeness’ of the structural features observed in a model and describes the likelihood that a given model is of comparable quality to experimental structures. Model quality estimates based on the QMEAN scoring function were normalized with respect to the number of interactions. The resulting scoring function is independent of the size of the protein and may therefore be used to assess both monomers and entire oligomeric assemblies. Model quality scores for individual models are then expressed as ‘ Z-scores’ in comparison to scores obtained for high-resolution crystal structures. We demonstrate the ability of the newly introduced QMEAN Z-score to detect experimentally solved protein structures containing significant errors, as well as to evaluate theoretical protein models.

          In a comprehensive QMEAN Z-score analysis of all experimental structures in the PDB, membrane proteins accumulate on one side of the score spectrum and thermostable proteins on the other. Proteins from the thermophilic organism Thermatoga maritima received significantly higher QMEAN Z-scores in a pairwise comparison with their homologous mesophilic counterparts, underlining the significance of the QMEAN Z-score as an estimate of protein stability.

          Availability: The Z-score calculation has been integrated in the QMEAN server available at: http://swissmodel.expasy.org/qmean.

          Contact: torsten.schwede@ 123456unibas.ch

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references59

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

          S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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            The Protein Data Bank.

            The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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              Inference of macromolecular assemblies from crystalline state.

              We discuss basic physical-chemical principles underlying the formation of stable macromolecular complexes, which in many cases are likely to be the biological units performing a certain physiological function. We also consider available theoretical approaches to the calculation of macromolecular affinity and entropy of complexation. The latter is shown to play an important role and make a major effect on complex size and symmetry. We develop a new method, based on chemical thermodynamics, for automatic detection of macromolecular assemblies in the Protein Data Bank (PDB) entries that are the results of X-ray diffraction experiments. As found, biological units may be recovered at 80-90% success rate, which makes X-ray crystallography an important source of experimental data on macromolecular complexes and protein-protein interactions. The method is implemented as a public WWW service.
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                Author and article information

                Journal
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                1 February 2011
                5 December 2010
                5 December 2010
                : 27
                : 3
                : 343-350
                Affiliations
                1Biozentrum, University of Basel and 2SIB Swiss Institute of Bioinformatics, Basel, Switzerland
                Author notes
                * To whom correspondence should be addressed.

                Associate Editor: Alfonso Valencia

                Article
                btq662
                10.1093/bioinformatics/btq662
                3031035
                21134891
                74efc337-d2b6-4e51-a358-feebbf720707
                © The Author(s) 2010. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 August 2010
                : 3 November 2010
                : 29 November 2010
                Categories
                Original Papers
                Structural Bioinformatics

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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