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

By Pascal Benkert, Marco Biasini, Torsten Schwede. 2010

2,179 citations recorded by the source corpus.

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@unibas.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Subfields: Materials Chemistry, Molecular Biology, Computational Biology & Bioinformatics

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Citations in the corpus

Comparative Protein Structure Modeling Using MODELLER (2016, background): “…(Luthy et al., 1992), Prosa, 2003 (Sippl, 1993; Wiederstein and Sippl, 2007), HARMONY (Topham et al., 1994), ANOLEA (Melo and Feytmans, 1998), DFIRE (Zhou and Zhou, 2002), DOPE (Shen and Sali, 2006), SOAP (Dong et al., 2013), QMEAN local (Benkert et al., 2011), and TSVMod (Eramian et al., 2008).”
Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal (2012, background): “The QMEAN Z-score is a quality estimate which relates structural features observed in a model to their expected distributions based on statistics for experimental protein structures of comparable size (54, 92).”
Automated tertiary structure prediction with accurate local model quality assessment using the intfold‐ts method (2011, background): “7,8 MQAPs exist as either standalone programs or as web servers and are generally used by predictors and experimentalists to evaluate 3D models after they have been generated by either fold recognition or free modeling (FM) servers.”
Protein Modelling: What Happened to the “Protein Structure Gap”? (2013, neutral): “, 1993) or apply a combination of knowledge-based statistical measures derived from high-resolution crystals structures to provide estimates of model accuracy (Benkert et al., 2011; Ray et al., 2012; Wiederstein and Sippl, 2007).”
Comparative Protein Structure Modeling Using MODELLER (2016, background): “…(Luthy et al., 1992), Prosa, 2003 (Sippl, 1993; Wiederstein and Sippl, 2007), HARMONY (Topham et al., 1994), ANOLEA (Melo and Feytmans, 1998), DFIRE (Zhou and Zhou, 2002), DOPE (Shen and Sali, 2006), SOAP (Dong et al., 2013), QMEAN local (Benkert et al., 2011), and TSVMod (Eramian et al., 2008).”
Improved model quality assessment using ProQ2 (2012, neutral): “The first of them is singlemodel methods that only use information from the actual model, such as evolutionary information [8-10], residue environment compatibility [11], statistical potentials from physics [12] or knowledge-based ones [13,14], or combinations of different structural features [15-19”
OpenStructure: an integrated software framework for computational structural biology (2013, methodology): “OpenStructure has been successfully used as an analysis and development platform in several recently published research projects, e.g. QMEAN (Benkert et al., 2011), the local difference distance test (Mariani, Kiefer et al., 2011), the identification of two-histidine one-carboxylate binding motifs i”
QMEANDisCo—distance constraints applied on model quality estimation (2019, methodology): “One established single model method is QMEAN (Benkert et al. , 2008, 2011).”