Skip to main content

Advertisement

Table 2 Comparison between QMEAN, various QMEANclust implementations and selfQMEAN on all CASP7 server models.

From: QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information

QMEAN implementation Pearson Spearman Sum(GDT)
QMEAN:    
QMEAN3 0.645 0.551 50.17
QMEAN3 * fraction modelled 0.663 0.605 51.92
QMEAN4 0.647 0.540 49.57
QMEAN4 * fraction modelled 0.671 0.609 52.65
QMEAN5 0.729 0.630 54.87
QMEAN5 * fraction modelled 0.740 0.676 55.32
QMEAN6 0.741 0.638 56.36
QMEAN6 * fraction modelled 0.752 0.684 56.70
QMEANclust: no preselection    
Median 0.872 0.812 56.64
Mean (~3D-jury based on GDT_TS) 0.889 0.821 57.16
Weighted mean 0.883 0.824 57.63
QMEANclust: QMEAN Z-score > x    
Median: Z-score > -1 0.877 0.815 57.05
Mean: Z-score > -1 0.876 0.817 57.30
Weighted mean: Z-score > -1 0.882 0.823 57.60
Median: Z-score > 0 0.884 0.824 57.52
Mean: Z-score > 0 0.879 0.822 57.35
Weighted mean: Z-score > 0 0.882 0.826 57.31
Median: Z-score > 0.5 0.885 0.828 57.33
Mean: Z-score > 0.5 0.880 0.830 56.96
Weighted mean: Z-score > 0.5 0.883 0.832 57.18
QMEANclust: top × percent models    
Median: 20% TBM, 20% FM 0.888 0.842 57.37
Median: 10% TBM, 10% FM 0.890 0.844 57.83
Median: 5% TBM, 5% FM 0.873 0.826 56.98
Median: 10% TBM, 20% FM 0.886 0.844 57.23
Median: 20% TBM, 10% FM 0.892 0.842 57.97
QMEANclust: ΔQMEAN-score from max    
Median: Δ < 0.05 Å TBM, Δ < 0.05 Å FM 0.867 0.826 57.65
Median: Δ < 0.1 Å TBM, Δ < 0.1 Å FM 0.892 0.837 57.69
Median: Δ < 0.05 Å TBM, Δ < 0.1 Å FM 0.892 0.841 58.11
Median: Δ < 0.1 Å TBM, Δ < 0.05 Å FM 0.868 0.822 57.23
selfQMEAN:    
Linear combination of 5 terms (w/o all-atom) 0.811 0.755 55.53
Sum of Z-scores (5 terms) 0.830 0.749 56.60
Sum of Z-scores (6 terms) 0.832 0.753 55.60
  1. Average correlation coefficient and total maximum GDT_TS score of the selected models of different QMEAN versions obtained on the test set containing all CASP7 server models. A description of all QMEAN versions is given in Table 1. For the QMEANclust consensus score, a multitude of strategies for pre-selecting reference models based on QMEAN score is investigated. The models of the reference set are defined based on a certain Z-score cut-off, by using only a percentage of top scoring models or by including only models being close to the highest scoring model. The different cut-offs used for template-based modelling targets (TBM) of free modelling targets (FM) are indicated. Underlined values are used in Table 3 for comparison to other methods. The selfQMEAN scoring function is based on ensemble-specific statistical potentials.