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. 2017 Jan;85(1):39-45.
doi: 10.1002/prot.25188. Epub 2016 Nov 13.

Structural quality of unrefined models in protein docking

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Structural quality of unrefined models in protein docking

Ivan Anishchenko et al. Proteins. 2017 Jan.

Abstract

Structural characterization of protein-protein interactions is essential for understanding life processes at the molecular level. However, only a fraction of protein interactions have experimentally resolved structures. Thus, reliable computational methods for structural modeling of protein interactions (protein docking) are important for generating such structures and understanding the principles of protein recognition. Template-based docking techniques that utilize structural similarity between target protein-protein interaction and cocrystallized protein-protein complexes (templates) are gaining popularity due to generally higher reliability than that of the template-free docking. However, the template-based approach lacks explicit penalties for intermolecular penetration, as opposed to the typical free docking where such penalty is inherent due to the shape complementarity paradigm. Thus, template-based docking models are commonly assumed to require special treatment to remove large structural penetrations. In this study, we compared clashes in the template-based and free docking of the same proteins, with crystallographically determined and modeled structures. The results show that for the less accurate protein models, free docking produces fewer clashes than the template-based approach. However, contrary to the common expectation, in acceptable and better quality docking models of unbound crystallographically determined proteins, the clashes in the template-based docking are comparable to those in the free docking, due to the overall higher quality of the template-based docking predictions. This suggests that the free docking refinement protocols can in principle be applied to the template-based docking predictions as well. Proteins 2016; 85:39-45. © 2016 Wiley Periodicals, Inc.

Keywords: interactome; model refinement; protein modeling; protein recognition; steric clash; structure prediction.

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Figures

Figure 1
Figure 1. Clashes in docking of unbound proteins
For 102 complexes in DOCKGROUND Benchmark 3, 2513 free docking and 134 template-based docking predictions of acceptable and higher quality were assessed by average (A) and maximum (B) penetrations, calculated from Eqs 1 and 2, respectively. Reference is the distribution of clashes in the 102 reference complexes obtained by superimposition of the two unbound protein structures onto corresponding proteins in the co-crystallized complex.
Figure 2
Figure 2. Side chain and backbone clashes in docking of unbound proteins
Volumes of intersections ΔVvdwatom(3) were calculated for each pair of overlapping atoms, based on their radii and the interatomic distance. The distributions were obtained for 201,422 and 12,827 pairs of side-chain atoms (A), 191,700 and 14,937 pairs of backbone and side-chain atoms (B), and 28,982 and 4,466 pairs of backbone atoms (C) in free and template-based docking, respectively.
Figure 3
Figure 3. Clashes in docking of different quality
Distributions of average penetrations (Eq. 1) are shown separately for high (A), medium (B), and acceptable (C) quality models (according to CAPRI criteria). Plots are obtained for 32, 514, 1967 free and 56, 48, 29 template-based high, medium, and acceptable quality predictions, respectively. The reference distributions were obtained from the analysis of clashes in random models. For each target with at least one free or template-based prediction within a certain quality category, ten random models (one for targets with acceptable free models) of the same quality were generated (see text and Figure 5).
Figure 4
Figure 4. Example of clashes in acceptable quality docking predictions
Docking was performed by free (A) and template-based (B) protocols. Unbound structures corresponding to 2nz8, chains A and B, from DOCKGROUND Benchmark 3 were used. The unbound structure 1mh1, chain A, is in blue, and the unbound structure 1nty, chain A is in red. Overlapping van der Waals volumes are in yellow. The interface side-chains selected at 3 Å cut-off are in sticks. Average, dav, and maximum, dmax, penetrations are 0.15 Å and 1.62 Å for the free and 0.58 Å and 3.80 Å for the template-based predictions, respectively.
Figure 5
Figure 5. Flowchart of random model generation
Given two proteins in their reference positions (overlapped with the co-crystallized monomers), and the intended quality Qtarget (high, medium, or acceptable), the procedure repeatedly generates a model by randomly translating (translation vector t⃗) and rotating (rotation matrix U) the ligand L with respect to the receptor R. At each trial, the quality Qnew of the complex RL’ is calculated. The procedure is repeated until the model with the intended quality is obtained.
Figure 6
Figure 6. Clashes in docking of modeled proteins
Protein models are from 165 complexes in the DOCKGROUND model set 2. Distributions of average penetrations, dav (Eq. 1), in the template-based (A) and free (B) docking predictions of acceptable and higher quality are shown separately for each accuracy level of protein models (1 to 6 Å RMSD from the corresponding native structures). For reference, the plot shows dav distribution of docking predictions from the co-crystallized bound proteins. The inset shows the mean values of the main panel distributions along with corresponding mean values of dav distributions in free docking of the same set of modeled proteins.

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