Improved model quality assessment using ProQ2

Abstract

BackgroundEmploying methods to assess the quality of modeled protein structures is now standard practice in bioinformatics. In a broad sense, the techniques can be divided into methods relying on consensus prediction on the one hand, and single-model methods on the other. Consensus methods frequently perform very well when there is a clear consensus, but this is not always the case. In particular, they frequently fail in selecting the best possible model in the hard cases (lacking consensus) or in the easy cases where models are very similar. In contrast, single-model methods do not suffer from these drawbacks and could potentially be applied on any protein of interest to assess quality or as a scoring function for sampling-based refinement.ResultsHere, we present a new single-model method, ProQ2, based on ideas from its predecessor, ProQ. ProQ2 is a model quality assessment algorithm that uses support vector machines to predict local as well as global quality of protein models. Improved performance is obtained by combining previously used features with updated structural and predicted features. The most important contribution can be attributed to the use of profile weighting of the residue specific features and the use features averaged over the whole model even though the prediction is still local.ConclusionsProQ2 is significantly better than its predecessors at detecting high quality models, improving the sum of Z-scores for the selected first-ranked models by 20% and 32% compared to the second-best single-model method in CASP8 and CASP9, respectively. The absolute quality assessment of the models at both local and global level is also improved. The Pearson’s correlation between the correct and local predicted score is improved from 0.59 to 0.70 on CASP8 and from 0.62 to 0.68 on CASP9; for global score to the correct GDT_TS from 0.75 to 0.80 and from 0.77 to 0.80 again compared to the second-best single methods in CASP8 and CASP9, respectively. ProQ2 is available at http://proq2.wallnerlab.org.

The methanogenic redox cofactor F420 is widely synthesized by aerobic soil bacteria

“…Phyre2 (Kelley et al, 2015) was used to model protein structures based on these sequences based on solved protein structures with highest percentage amino acid sequence identity. The quality of the models at the global (full protein) and local (F 420 -binding site) scales were assessed using ProQ2 (Ray et al, 2012). F 420 -binding motifs were identified based on previous studies (Eguchi et al, 1984;Purwantini and Daniels, 1998;Aufhammer et al, 2004;Ahmed et al, 2015).…”

Structural Model of the Anion Exchanger 1 (SLC4A1) and Identification of Transmembrane Segments Forming the Transport Site

“…Nowadays, the tools, like QMEAN server, one of the most efficient tool available for assessing the accuracy of a structural model, are not appropriate to validate a transmembrane protein model (23). ProQM, the only tool available to assess membrane protein models, indicated that the quality of the model is medium (24). However, the present model provides useful information regarding helix spatial organization that should be further validated experimentally.…”

Structural and Functional Attributes of the Interleukin-36 Receptor

“…ProQ2 (29) did not flag serious problems in the local or global quality of the homology models. Minor issues that were identified tended to occur in longer turns or loops.…”