A flexible docking scheme to explore the binding selectivity of PDZ domains

Abstract

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

Figure 1

(A) The procedure of the docking protocol. The deformed structures of the unbound structure are obtained moving along the mode with ENM. Then, a large set of conformations starting from these structures is generated using the dihedral restrained REMD. RosettaLigand is used for self- and cross-docking runs (see “Materials and Methods” for details). (B) As case study of PSD95, we tested the docking performance of the conformations obtained at each step shown in (A) by simply docking Class I and Class I peptides. The RMSD values of the peptides and binding energy values are given. Overall, the docking performance gets better as we further follow the steps. [Color figure can be viewed in the online issue, which is available at http://www.interscience.wiley.com.]

Figure 2

The binding energy score versus RMSD of the docked complex for (A) PSD-95 and (B) GRIP. Docking Class I and Class II peptides to the unbound conformation of PSD-95 does not discriminate the selectivity preference [brown (Class I) and red (Class II) dots in the plots]. However, when ENM-REMD snapshots are used (i.e., when the backbone flexibility is also considered), our flexible scheme does a better job than simply docking to the unbound structure of PSD-95 [blue (Class I) and cyan (Class II) dots in the plots]. (C) The comparison of docking Class I peptide to the unbound structure (upper figure) and the ENM-REMD snapshot (lower figure) is shown as ribbon diagrams. Green represents the actual binding mode in both docking, whereas blue and brown ones are for the docked peptide conformations corresponding to the lowest binding energies of ENM-REMD snapshot and the unbound structure, respectively. (D) Ribbon diagrams for docking Class II type of peptide to the unbound conformation and ENM-REMD conformation by RosettaLigand. [Color figure can be viewed in the online issue, which is available at http://www.interscience.wiley.com.]

Figure 3

The binding energy score versus RMSD of the docked complex for (A) Syntenin and (B) Erbin that have dual specificities. Docking Class I and Class II peptides to the unbound conformations of Syntenin and Erbin does not discriminate the selectivity preference [brown (Class I) and red (Class II) dots in the plots]. When ENM-REMD conformations are used, Syntenin binds slightly better to the Class II peptide (cyan dots) than to the Class I peptide (blue dots) whereas Erbin binds Class I peptide with higher affinity than the Class II peptide (blue and cyan dots in the plots). (C) The corresponding lowest energy structures of docking Class II peptide to the unbound structure (upper figure) and the ENM-REMD snapshot (lower figure) of Syntenin are displayed as ribbon diagrams along with actual peptide (green). (D) Docking Class I peptide to the best pose obtained for the unbound structure (upper figure) and the ENM-REMD snapshot (lower figure) of Erbin are presented. [Color figure can be viewed in the online issue, which is available at http://www.interscience.wiley.com.]

Figure 4

The binding energy score versus RMSD of the docked complex for PICK1. Wild-type PICK1 (A) prefers Class II type of peptide sequence while K25E mutation (B) and K83H mutation (C) on PICK1 alter its binding specificity to Class I type of peptide sequences. Docking Class I and Class II peptides to the unbound conformation of wild and mutant PICK1 does not show the change in selectivity upon mutation [brown (Class I) and red (Class II) dots in the plots]. However, when REMD-ENM conformations are used, wild type has a higher affinity for Class II type peptide binding [cyan on (A)] whereas both mutants prefer Class I type of peptide [blue on (B) and (C)]. The corresponding lowest energy structures of PDZ-peptide complexes are represented as ribbon diagrams along with experimental peptide position. [Color figure can be viewed in the online issue, which is available at http://www.interscience.wiley.com.]