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. 2017 Mar;85(3):470-478.
doi: 10.1002/prot.25183. Epub 2016 Oct 24.

Modeling complexes of modeled proteins

Ivan Anishchenko  1 , Petras J Kundrotas  1 , Ilya A Vakser  1   2
Affiliations

Modeling complexes of modeled proteins

Ivan Anishchenko et al. Proteins. 2017 Mar.

Abstract

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å Cα RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc.

Keywords: interactome; protein docking; protein modeling; protein recognition; structure prediction.

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Figures

Figure 1
Figure 1. Distribution of near-native and false-positive matches according to the accuracy of protein models
The top 1000 free docking (A) and all template-based docking (B) predictions, for each of the 165 complexes from the Models Docking Benchmark 2, at each of the six accuracy levels, were compared to the corresponding “ideal” complexes (see Methods) in terms of I-RMSD. In the docking of the X-ray structures, comparisons were made to the corresponding native X-ray structures. Near-native matches were defined as those with I-RMSD < 4 Å.
Figure 2
Figure 2. Docking success rates for protein models compared to the success rates for X-ray structures
Successfully predicted complexes (those for which at least one acceptable or better quality prediction is among the top 10 docking poses), in the free docking (left hand panel) and the template-based docking (right hand panel) are in dark gray. Complexes with successful predictions by the X-ray docking only are in light gray. Complexes with successful predictions by the models docking only are in dashed bars. The quality of the models docking was accessed relative to the “ideal” complexes (see Methods). The data are normalized by the total numbers of complexes in all three categories shown on top of the bars.
Figure 3
Figure 3. Conservation of templates in template-based docking of models
Dark gray bars show templates common for the docking predictions of the X-ray structures and docking predictions of the corresponding models. Light gray bars show templates for the docking of the X-ray structures predictions only. Dashed bars show templates for the docking of the models predictions only. Data for good (acceptable or higher quality) predictions (A), and incorrect predictions (B) is normalized by the total number of templates shown on top of the bars.
Figure 4
Figure 4. Comparison of free and template-based docking of models predictions with the docking of X-ray structures predictions in terms of fraction of shared contacts
For each level of the model accuracy and each complex in the set, docking prediction of the X-ray structure with the maximum fraction of shared contacts FSCij (Eq. 2) was used for comparison with each of the top 1000 free docking of the models predictions. The resulting 165×1000 FSCij scores were plotted as gray box-and-whisker diagrams, separately for each distortion level (A). Box areas and whiskers contain 25 – 75 % and 5 – 95 % of data, respectively (outliers not shown). Lower bounds (blue) were estimated using 1000 randomly selected matches from the top 100,000 free docking of the models predictions. Upper bounds (red) were evaluated on a 1000-matches subset among 100,000 free docking of the models predictions with the maximum FSCij similarity to the top 1000 docking of the X-ray structures predictions. Darker and lighter areas of the upper and lower bounds correspond to boxes and whiskers respectively, and the dashed lines indicate medians. For the template-based docking (B), only pairs of the model and the X-ray predictions that share the same template (dark gray bars in Figure 3, and numbers at the whiskers in this figure) were considered. Upper and lower limits for the template-based docking were not estimated due to a statistically insufficient number of the docking predictions.
Figure 5
Figure 5. Example of clustering in free and template-based docking
Co-crystallized structures of the 1dlf chains H and L, along with their models at the six levels of accuracy from the Benchmark 2 were used in the free (left-hand panel) and the template-based (right-hand panel) docking. Top 1000 free and all template-based predictions are shown. Predicted matches are shown by yellow spheres, corresponding to the ligand (L chain) native interface center of mass. Magenta sphere corresponds to the native interface. The receptor structure (H chain) shown in cartoon is color-coded to reveal the location of distortions and their level. Distortions are measured as Cα-Cα distances calculated from RMSD-based superposition of the model onto the corresponding monomer from the co-crystallized complex.
Figure 6
Figure 6. Normalized success rates for the template-based and the free docking
The free docking at low resolution was performed by GRAMM, and at high resolution by ZDOCK 3.0.2. The complex was predicted successfully if one out of the top 10 predictions was correct (acceptable, medium or high quality). All success rates are normalized by the ones for the co-crystallized X-ray structures. The numbers above the data points show the absolute number of successful docking outcomes (out of 165 complexes in Benchmark 2).
Figure 7
Figure 7. Docking success rates for different number of top solutions
The successful prediction was defined as one correct structure (acceptable, medium or high quality) in the top N predictions. The rates are shown for the free (A) and the template-based docking (B).
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