Section: New Results

Prediction of homo- and hetero-protein complexes by ab-initio and template-based docking: a CASP-CAPRI experiment

Participants : Sergei Grudinin, Petr Popov, Emilie Neveu.

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures offer a clear advantage over standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy.

Most of the targets in Round 30 of CAPRI were homodimers and homotetramers, thus it was a good opportunity to test our novel symmetry assembling docking method. To do so, we imposed C2 symmetry constraints for all the homodimers and we imposed C4 and D2 symmetry constraints for all the homotetramers from the target complexes. Below, we present the new fast multi-resolution method for docking both symmetric and non-symmetric protein complexes that was used in Round 30 of CAPRI. First, the structures of the individual subunits were taken from the stage two predictions of the CASP10 assessment experiment. More precisely, starting from 150 available CASP 3D models of monomers, we predicted models of symmetric multimers using the novel symmetry docking method, which performs symmetry-induced protein docking using the shape-complementarity scoring function computed as spherical polar Fourier correlations. Specifically, this method performs exhaustive search over the available (four in case of cyclic symmetries or six otherwise) degrees of freedom for the given point group symmetry type. For the targets of Round 30 of CAPRI we imposed three types of symmetry, C2, C4, and D2. For the case of heterodimers, we used the standard Hex docking method.

For the input of the docking methods, we generated the scaffolds of initial models of monomers by cutting-off the side chains. More specifically, we mutated all side-chains except for the glycines to alanines. Compared to the standard all-atom rigid-body docking methods, we expect the scaffold docking approach to produce binding poses that are less sensitive to the flexibility of the side-chains. We clustered the solutions with the threshold ligand-RMSD value of 8 Åusing the RigidRMSD library. Finally, we ranked the clusters by the value of the best score and kept 50 best clusters for the refinement stage. In total, for each target we proceeded to the refinement with 7,500 modeled structures of protein complexes.

On the next step, we optimized each putative binding interface of the all-atom representation of a protein complex by means of a rigid-body first-order minimization scheme. Specifically, after each rigid-body minimization step we proceeded with the optimization of side-chains described by the rotameric representation using the SCWRL4 package. We computed the interactions between the subunits in a protein complex using the novel reference state-free knowledge-based scoring function KSENIA, which is smooth by construction and is thus very suitable for a gradient-based minimization protocol. Finally, we ranked the predictions by the value of the KSENIA potential of the optimized structure and selected ten best candidates for the submission.