Structural modeling of protein interactions by analogy: application to PSD-95

Abstract

We describe comparative patch analysis for modeling the structures of multidomain proteins and protein complexes, and apply it to the PSD-95 protein. Comparative patch analysis is a hybrid of comparative modeling based on a template complex and protein docking, with a greater applicability than comparative modeling and a higher accuracy than docking. It relies on structurally defined interactions of each of the complex components, or their homologs, with any other protein, irrespective of its fold. For each component, its known binding modes with other proteins of any fold are collected and expanded by the known binding modes of its homologs. These modes are then used to restrain conventional molecular docking, resulting in a set of binary domain complexes that are subsequently ranked by geometric complementarity and a statistical potential. The method is evaluated by predicting 20 binary complexes of known structure. It is able to correctly identify the binding mode in 70% of the benchmark complexes compared with 30% for protein docking. We applied comparative patch analysis to model the complex of the third PSD-95, DLG, and ZO-1 (PDZ) domain and the SH3-GK domains in the PSD-95 protein, whose structure is unknown. In the first predicted configuration of the domains, PDZ interacts with SH3, leaving both the GMP-binding site of guanylate kinase (GK) and the C-terminus binding cleft of PDZ accessible, while in the second configuration PDZ interacts with GK, burying both binding sites. We suggest that the two alternate configurations correspond to the different functional forms of PSD-95 and provide a possible structural description for the experimentally observed cooperative folding transitions in PSD-95 and its homologs. More generally, we expect that comparative patch analysis will provide useful spatial restraints for the structural characterization of an increasing number of binary and higher-order protein complexes.

Figure 1. Basic Steps of Comparative Patch Analysis Approach

First, the binding sites of the homologs of each domain are extracted from PIBASE and superposed on its surface. Second, for each pair of the superposed binding sites, we apply a restrained docking of the domains with PatchDock to obtain a set of candidate binary domain complexes. Each of the binary complexes is then ranked using geometrical complementarity and statistical potential, and the top-ranked complex is selected to be a final prediction.

Figure 2. Examples of Predicted Protein Interface between Two Subunits for a Pyruvate Formate–Lyase Protein Complex from Our Benchmark Set

Shown are the structures of the native complex (grey) together with the best-scoring models that were predicted by comparative patch analysis using binding site information for (A) both, or (B) just one of the interacting subunits, and (C) by conventional protein docking, where no binding site information is provided. The predicted and native structures are superposed using one of the two subunits, which is represented by its accessible surface. The remaining subunits of the predicted structures are shown in the ribbon representation colored red, blue, and orange, correspondingly. In both scenarios, comparative patch analysis was significantly more accurate than protein docking. Using both binding sites, comparative patch analysis accurately predicted the protein interaction interface, including the relative orientation of subunits. The accuracy of interface prediction by our approach using only one binding site was significantly reduced, while it was still able to predict the binding sites near their native locations. The conventional protein docking failed to accurately predict either the relative orientation of subunits or the locations of their binding sites.

Figure 3. Two Binding Modes of the Core Fragment of Rat PSD-95

The PDZ₃ domain is shown in blue, SH3 in red, and GK in yellow. The grey spheres correspond to the residues of the interdomain linker between PDZ₃ and SH3. Locations of the hydrophobic cleft (Cleft) and PXXP motif (PXXP) in PDZ₃, PRBS in SH3, and the GBS in GK are shown by arrows. (A) The domain architecture of the core fragment. (B) The first predicted configuration. (C) The second predicted configuration. The difference between the theoretically calculated SAXS spectra of the first (red) and second (blue) configurations is significantly larger than the anticipated experimental error.

Figure 4. The Localization of Binding Sites for Both Modeled Configurations of the PDZ₃–SH3–GK Core Fragment Compared with Protein Docking

Top ten scoring models were selected for both interactions (PDZ₃–SH3, PDZ₃–GK) obtained using comparative patch analysis and using conventional protein docking. The localization index δ_I of a residue defines the relative frequency of its participation in the interaction interface. The residues that are colored grey do not participate in the interface of any of the top ten models. The PRBS in SH3 and the GBS in GK are shown by arrows.

Figure 5. The PDZ₃–SH3–GK and SH3–GK Domains Are Stable Fragments

(A) Coomassie-stained gel (10% acrylamide) of aliquots from limited proteolysis of PSD-95 by Subtilisin proteinase: panels 1 and 3, Precision Plus Protein molecular weight marker (Bio-Rad, http://www.bio-rad.com); panel 2, starting sample prior to proteinase addition; panels 4, Lanes 4–9, Aliquots at 5, 30, 60, 90, 120 min, and 8 h after protease addition (as labeled). Arrows point to stable fragments that were excised from the gel and analyzed by mass spectrometry as described in Methods. (B) Sequence of Rat PSD-95: underlined are the peptide sequences identified by mass spectrometry from the ∼34 kDa stable fragment corresponding to residues 429–721 (33,944 kDa). In bold are the sequences derived from the ∼48 kDa stable fragment comprising residues 300–721 (47,796 kDa).