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. 2010 Feb;58(2):515-27.
doi: 10.1016/j.neuropharm.2009.08.019. Epub 2009 Sep 6.

Exploring kainate receptor pharmacology using molecular dynamics simulations

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Exploring kainate receptor pharmacology using molecular dynamics simulations

Pekka A Postila et al. Neuropharmacology. 2010 Feb.

Abstract

Ionotropic glutamate receptors (iGluRs) are enticing targets for pharmaceutical research; however, the search for selective ligands is a laborious experimental process. Here we introduce a purely computational procedure as an approach to evaluate ligand-iGluR pharmacology. The ligands are docked into the closed ligand-binding domain and during the molecular dynamics (MD) simulation the bi-lobed interface either opens (partial agonist/antagonist) or stays closed (agonist) according to the properties of the ligand. The procedure is tested with closely related set of analogs of the marine toxin dysiherbaine bound to GluK1 kainate receptor. The modeling is set against the abundant binding data and electrophysiological analyses to test reproducibility and predictive value of the procedure. The MD simulations produce detailed binding modes for analogs, which in turn are used to define structure-activity relationships. The simulations suggest correctly that majority of the analogs induce full domain closure (agonists) but also distinguish exceptions generated by partial agonists and antagonists. Moreover, we report ligand-induced opening of the GluK1 ligand-binding domain in free MD simulations. The strong correlation between in silico analysis and the experimental data imply that MD simulations can be utilized as a predictive tool for iGluR pharmacology and functional classification of ligands.

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Figures

Fig. 1
Fig. 1
The 2D structures of all simulated ligands. The carbon atom numbering used for DH analogs is shown for boxed neoDH.
Fig. 2
Fig. 2
The binding mode of DH. In (A) the 2D structure of DH with five key binding groups (a–e) are highlighted and in (B) the binding interactions of DH with GluK1–LBC are shown in detail. (a) The side chain guanidinium group of Arg523 and Ser689N, and Thr518N hydrogen bond to the α-carboxylate group of DH and the side chain carboxylate group of Glu738, the side chain hydroxyl of Thr518, and Pro516O hydrogen bond to the α-amine group of DH. (b) Thr690N and the side chain hydroxyl of Thr690 hydrogen bond to the γ-carboxylate group of DH. (c) The C8 aminomethyl group hydrogen bonds to the side chain hydroxyl of Ser741 and the side chain carboxylate group of Glu738, and (d) the C9 hydroxyl of the ring system hydrogen bond to Glu738N. (e) The tetrahydrofuropyran ring (referred as the ring system) of DH hydrophobically packs against the side chains of the binding pocket residues Tyr489, Glu441, and Pro516 at the D1 face of the binding pocket. The hydrogen bonds are shown as green dotted lines, the yellow line represent intra-ligand hydrogen bonds, the orange lines highlight the hydrogen bonds between the side chains of Glu441 and Ser721, and the purple line connect Glu738N to the C9 hydroxyl. The solvent accessible surface (transparent surface) visualizes the hydrophobic face. Amino acids at the D1 face are shown with white carbon atoms and at the D2 face with black carbon atoms. The oxygen atom of the water molecule is presented as red sphere, and the ligand skeleton is shown as yellow ball-and-stick representation.
Fig. 3
Fig. 3
The atom pairs in the D1 and D2 lobes of the GluK1–LBC ligand-binding pocket selected for distance measurements from MD trajectories. The D1–D2 atom pairs indicated by dotted lines include: Glu441-Ser721, Thr518-Ser689, Pro516O-Glu738, and Gly490O-Asp687N. The bound (S)-glutamate skeleton is shown as a black ball-and-stick representation. The D2 is shown with darker color than the D1.
Fig. 4
Fig. 4
The binding modes of DH-based high affinity agonist ligands into GluK1–LBC: (A) neoDH, (B) 8-deoxy-neoDH, (C) 8-epi-neoDH, and (D) 9-F-8-epi-neoDH. For coloring and interpretation see Fig. 2B.
Fig. 5
Fig. 5
The distances (four leftmost panels) and domain closure angles (the rightmost panel) showing the D1–D2 separation and opening of the closed GluK1–LBC in complex with (A) 8-deoxy-neoDH, (B) (S)-glutamate, (C) 9-deoxy-neoDH, (D) domoate, (E) LY466195, (F) 4-epi-neoDH, (G) 2,4-epi-neoDH, (H) MSVIII-19, and (I) without a bound ligand. On the x axis is presented the timescale (ns) and on the y axis the distance (Å) as 100-moving average or receptor cleft closure angle degree. See Fig. 3 for details on the atoms used in the distance measurements. The measurements for A chain of the GluK1–LBC dimer are shown with darker color than for B chain.
Fig. 6
Fig. 6
The binding modes of DH-based low affinity (or partial) agonist ligands for GluK1: (A) 9-deoxy-neoDH, (C) 9-epi-neoDH, (D) 8,9-epi-neoDH, and (E) 4-epi-neoDH. For coloring and interpretation (A, C–E) see Fig. 2B. In (B) is compared the crystal structures of two partial agonist–LBC complexes, GluA2–kainate (yellow) and GluK1–domoate (orange), agonist–LBC complex GluK1–DH (purple), and the MD simulated GluK1–9-deoxy-neoDH complex (pink). The structure comparison shows that 9-deoxy-neoDH is likely a partial agonist for GluK1, because its receptor-bound conformation resembles more the partial agonist structures than that of natural agonist DH (purple ball-and-stick).
Fig. 7
Fig. 7
The binding modes of 2,4-epi-neoDH (A) and MSVIII-19 (C), and their effect on the GluK1–LBC opening (B) and (D), respectively. In (C), in the B chain (upper panel) the side chains of Glu441 and Ser721 are hydrogen bonded but in the A chain (lower panel) the bond does not exist. In (B), the crystal structure and MD simulation of GluK1–LY466195 complex is also shown. In (B) crystal structures of GluA2-kainate (partial agonist) and GluK1-LY466195 (antagonist) were used. In (D) crystal structures of GluK1-Glutamate (agonist) and GluA2-kainate (partial agonist) were used. For coloring and interpretation of panels (A) and (C), see Fig. 2B.

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