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. 2012 Nov 2;287(45):37745-56.
doi: 10.1074/jbc.M112.388157. Epub 2012 Aug 29.

High selectivity of the γ-aminobutyric acid transporter 2 (GAT-2, SLC6A13) revealed by structure-based approach

Affiliations

High selectivity of the γ-aminobutyric acid transporter 2 (GAT-2, SLC6A13) revealed by structure-based approach

Avner Schlessinger et al. J Biol Chem. .

Abstract

The solute carrier 6 (SLC6) is a family of ion-dependent transporters that mediate uptake into the cell of osmolytes such as neurotransmitters and amino acids. Four SLC6 members transport GABA, a key neurotransmitter that triggers inhibitory signaling pathways via various receptors (e.g., GABA(A)). The GABA transporters (GATs) regulate the concentration of GABA available for signaling and are thus targeted by a variety of anticonvulsant and relaxant drugs. Here, we characterize GAT-2, a transporter that plays a role in peripheral GABAergic mechanisms, by constructing comparative structural models based on crystallographic structures of the leucine transporter LeuT. Models of GAT-2 in two different conformations were constructed and experimentally validated, using site-directed mutagenesis. Computational screening of 594,166 compounds including drugs, metabolites, and fragment-like molecules from the ZINC database revealed distinct ligands for the two GAT-2 models. 31 small molecules, including high scoring compounds and molecules chemically related to known and predicted GAT-2 ligands, were experimentally tested in inhibition assays. Twelve ligands were found, six of which were chemically novel (e.g., homotaurine). Our results suggest that GAT-2 is a high selectivity/low affinity transporter that is resistant to inhibition by typical GABAergic inhibitors. Finally, we compared the binding site of GAT-2 with those of other SLC6 members, including the norepinephrine transporter and other GATs, to identify ligand specificity determinants for this family. Our combined approach may be useful for characterizing interactions between small molecules and other membrane proteins, as well as for describing substrate specificities in other protein families.

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Figures

FIGURE 1.
FIGURE 1.
GAT-2-GABA models and their validation by ligand enrichment. A and B, predicted structures of the GAT-2-GABA complex in the occluded (A) and the outward facing (B) conformations. GABA is colored in cyan, with oxygen, nitrogen, and hydrogen atoms in red, blue, and white, respectively. The sodium ions Na1 and Na2 are visualized as purple spheres. The transmembrane helices of GAT-2 are depicted as white ribbons. Key residues are displayed as sticks. The hydrogen bonds between GABA and GAT-2 are shown as dotted gray lines; they involve the residues Glu-48, Gly-51, and Gly-53, as well as the sodium ion Na1 for both conformations models. GABA forms polar interactions with Asn-54 only in the occluded conformation model. C and D, enrichment plots for different structures of the occluded (C) and the outward facing (D) models: the refined GAT-2 models (blue), random selection (red), the initial GAT-2 models (green), and the LeuT template structures (orange).
FIGURE 2.
FIGURE 2.
Validating predicted binding site residues by mutagenesis. Influence of site-directed mutations on 3H-GABA transport as compared with the wild-type sequence (GAT-2) and empty vector (EV). These results were obtained using HEK293 cells transiently transfected with the reference and mutated pcDNA5/FRT-GAT-2 or with the empty vector pcDNA5/FRT.
FIGURE 3.
FIGURE 3.
Chemical similarity network of predicted ligands. The relationships among the top ranked small molecule drugs from KEGG DRUG are visualized using Cytoscape 2.8.1. The nodes represent the small molecules predicted to bind GAT-2, using the occluded model (blue), the outward facing model (yellow), or both models (green). Each edge represents pairwise chemical similarity with Tc of at least 0.3. A, a similarity network using the edge-weighted spring-embedded layout algorithm in Cytoscape, which preserves all the relationships among the small molecules (49). B, a network with the 13 clusters of the small molecule drugs. The molecules were clustered using the Markov clustering algorithm (51) in Cytoscape. Representative small molecules structures of the clusters are visualized using MarvinView 5.4.1.1.
FIGURE 4.
FIGURE 4.
Predicted binding modes for GAT-2 validated ligands. A–D, predicted binding modes of newly identified GAT-2 ligands with GAT-2 models in the occluded (A and B) and the outward facing (C and D) conformations. Ligands are colored in cyan, with sulfur, chloride, oxygen, nitrogen, and hydrogen atoms in yellow, green, red, blue, and white, respectively. The sodium ions Na1 and Na2 are visualized as purple spheres. The transmembrane helices of GAT-2 are depicted as white ribbons. Key residues are displayed as sticks; the hydrogen bonds between ligands and key GAT-2 residues (e.g., Glu-48) are shown as dotted gray lines. The representative previously unknown ligands are homotaurine (A and C), GABOB (B), and baclofen (D).
FIGURE 5.
FIGURE 5.
cis-Inhibition studies of predicted GAT-2 inhibitors. Uptake of 3H-GABA in transiently transfected GAT-2-expressing HEK293 cells in the presence of various small molecule compounds is shown. The tested concentrations were 50 and 500 μm. A concentration of 5000 μm was only used where solubility and toxicity allowed. All of the data are shown with bars representing the S.E.
FIGURE 6.
FIGURE 6.
Comparison of GAT-2 and NET predicted binding sites. The final model of GAT-2 (A, white) and the model of NET (36) (B, blue) in the occluded conformation are shown with their corresponding substrates (i.e., GABA and norepinephrine, respectively) (yellow). Atoms are illustrated by sticks, with oxygen, nitrogen, and hydrogen atoms in red, blue, and white, respectively. The sodium ions Na1 and Na2 are visualized as purple spheres. GABA and norepinephrine are depicted in orange sticks, and their hydrogen bonds with GAT-2 (involving Glu-48, Gly-51, Gly-53, Asn-54, and Na1) and NET (involving Ala-145, Phe-72, and Asp-75) are shown as dotted gray lines.

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