Molecular Modeling of the Interactions of Glutamate Carboxypeptidase II with Its Potent NAAG-Based Inhibitors

Abstract

Glutamate carboxypeptidase II (GCPII, NAALADase, or NAAG peptidase) is a catalytic zinc metallopeptidase. Its extracellular domain hydrolyzes the abundant neuropeptide, N-acetyl-L-aspartyl-L-glutamate (NAAG), to produce N-acetylaspartate and glutamate following the synaptic release of this transmitter. Thus, GCPII influences the extracellular concentrations of both glutamate and NAAG. NAAG activates group II metabotropic glutamate receptors, and activation of this receptor has been found to protect against anoxia-induced excitotoxic nerve cell death. In contrast, high levels of glutamate can be neurotoxic. Thus, GCPII is a potential therapeutic target for the reduction of excitotoxic levels of glutamate and enhancement of extracellular NAAG. To explore the structural basis of the interaction between GCPII and its inhibitors, we modeled the three-dimensional structure of the GCPII extracellular domain using a homology modeling approach. On the basis of the GCPII model, the structures of GCPII in complex with its potent inhibitors 2-(phosphonomethyl)pentanedioic acid (PMPA) and 4,4'-phosphinicobis(butane-1,3-dicarboxylic acid) (PBDA) were built by a computational docking method. The model of GCPII mainly consists of two alpha/beta/alpha sandwiches, between which two zinc ions are quadrivalently coordinated by the His379-Asp389-Asp455-H(2)O and the Asp389-Glu427-His555-H(2)O clusters, respectively. The ligand binding pocket is situated between these two sandwiches and is comprised of two subpockets: one is a surface-exposed highly positively charged subpocket; the other is a buried hydrophobic subpocket. The positively charged subpocket can accommodate the pharmacophore groups of inhibitor molecules (PMPA and PBDA) through the coordination of Zn(2+) with their phosphorus functionality and hydrogen-bonding interactions with Arg536, Arg538, and Ser456 (or Asn521), while the hydrophobic subpocket is engaged in hydrophobic and hydrogen-bonding interactions with the nonpharmacophore groups of PBDA. The predicted binding mode is consistent with the experimental data obtained from site-directed mutagenesis. On the basis of the predicted interaction mode, our structure-based design has led to a series of highly potent GCPII inhibitors.

Radiolabeled Small-Molecule Ligands for Prostate-Specific Membrane Antigen: In vivo Imaging in Experimental Models of Prostate Cancer

“…It is the NAAG peptidase (NAALADase) activity of GCPII that confers the PSMA-binding characteristics to these compounds because PSMA and NAALADase are the same enzyme (24,25). DCMC and DCIT are not substrates for PSMA but are believed to bind electrostatically to the active site (26) so that PSMA is essentially behaving as a receptor for these ligands. The K i values of DCMC and DCIT are 1.9 and 1.5 nmol/L, respectively, well within the range necessary for successful receptor-based radiopharmaceuticals (27).…”

An insight into the sequential, structural and phylogenetic properties of banana 1-aminocyclopropane-1-carboxylate synthase 1 and study of its interaction with pyridoxal-5′-phosphate and aminoethoxyvinylglycine

“…Several studies have been described in the literature that apply homology models of proteins to explain putative protein-ligand interactions (Bourdon et al 1997;Escherich et al 2000;Garcia-Nieto et al 2000;Le Novere et al 2002). In some cases, the models were also subsequently used for designing new potent inhibitors (Kiyama et al 1999;Rong et al 2002;Tiraboschi et al 1999). Structural and biochemical data are necessary for designing ACC synthase inhibitors, whose applications are expected to have immense agricultural effects on controlling banana fruit ripening.…”

Mass spectrometry and non-covalent protein-ligand complexes: Confirmation of binding sites and changes in tertiary structure

“…NMR and X-ray crystallography have been the primary analytical tools used to obtain detailed atomic-level characterization of protein-ligand interactions. Computational modeling using homology [35], docking or solvation [36], or grid [37] based methods is also playing a key role in identifying regions on proteins that may serve as a binding site as well as predicting what molecules will bind to that site. In this study, we have developed a high throughput time resolved limited proteolysis MALDI MS method to confirm doxorubicin's computationally predicted binding site to TetC [29].…”