The "receiver operating characteristic" (ROC) curve method is a well-recognized metric used as an objective way to evaluate the ability of a given test to discriminate between two populations. This facilitates decision-making in a plethora of fields in which a wrong judgment may have serious consequences including clinical diagnosis, public safety, travel security, and economic strategies. When virtual screening is used to speed-up the drug discovery process in pharmaceutical research, taking the right decision upon selecting or discarding a molecule prior to in vitro evaluation is of paramount importance. Characterizing both the ability of a virtual screening workflow to select active molecules and the ability to discard inactive ones, the ROC curve approach is well suited for this critical decision gate. As a case study, the first virtual screening workflow focused on metabotropic glutamate receptor subtype 4 (mGlu4R) agonists is reported here. Six compounds out of 38 selected and tested in vitro were shown to have agonist activity on this target of therapeutic interest.

The gamma-amino-n-butyric acid type B (GABA(B)) receptor is composed of two subunits, GABA(B)1 and GABA(B)2, belonging to the family 3 heptahelix receptors. These proteins possess two domains, a seven transmembrane core and an extracellular domain containing the agonist binding site. This binding domain is likely to fold like bacterial periplasmic binding proteins that are constituted of two lobes that close upon ligand binding. Here, using molecular modeling and site-directed mutagenesis, we have identified residues in the GABA(B)1 subunit that are critical for agonist binding and activation of the heteromeric receptor. Our data suggest that two residues (Ser(246) and Asp(471)) located within lobe I form H bonds and a salt bridge with carboxylic and amino groups of GABA, respectively, demonstrating the pivotal role of lobe I in agonist binding. Interestingly, our data also suggest that a residue within lobe II (Tyr(366)) interacts with the agonists in a closed form model of the binding domain, and its mutation into Ala converts the agonist baclofen into an antagonist. These data demonstrate the pivotal role played by the GABA(B)1 subunit in the activation of the heteromeric GABA(B) receptor and are consistent with the idea that a closed state of the binding domain of family 3 receptors is required for their activation.

Ligand profiling is an emerging computational method for predicting the most likely targets of a bioactive compound and therefore anticipating adverse reactions, side effects and drug repurposing. A few encouraging successes have already been reported using ligand 2-D similarity searches and protein-ligand docking. The current study describes the use of receptor-ligand-derived pharmacophore searches as a tool to link ligands to putative targets. A database of 68,056 pharmacophores was first derived from 8,166 high-resolution protein-ligand complexes. In order to limit the number of queries, a maximum of 10 pharmacophores was generated for each complex according to their predicted selectivity. Pharmacophore search was compared to ligand-centric (2-D and 3-D similarity searches) and docking methods in profiling a set of 157 diverse ligands against a panel of 2,556 unique targets of known X-ray structure. As expected, ligand-based methods outperformed, in most of the cases, structure-based approaches in ranking the true targets among the top 1% scoring entries. However, we could identify ligands for which only a single method was successful. Receptor-ligand-based pharmacophore search is notably a fast and reliable alternative to docking when few ligand information is available for some targets. Overall, the present study suggests that a workflow using the best profiling method according to the protein-ligand context is the best strategy to follow. We notably present concrete guidelines for selecting the optimal computational method according to simple ligand and binding site properties.

Metabotropic glutamate (mGlu) receptors are promising targets to treat numerous brain disorders. So far, allosteric modulators are the only subtype selective ligands, but pure agonists still have strong therapeutic potential. Here, we aimed at investigating the possibility of developing subtype-selective agonists by extending the glutamate-like structure to hit a nonconsensus binding area. We report the properties of the first mGlu4-selective orthosteric agonist, derived from a virtual screening hit, LSP4-2022 using cell-based assays with recombinant mGlu receptors [EC(50): 0.11 ± 0.02, 11.6 ± 1.9, 29.2 ± 4.2 μM (n>19) in calcium assays on mGlu4, mGlu7, and mGlu8 receptors, respectively, with no activity at the group I and -II mGlu receptors at 100 μM]. LSP4-2022 inhibits neurotransmission in cerebellar slices from wild-type but not mGlu4 receptor-knockout mice. In vivo, it possesses antiparkinsonian properties after central or systemic administration in a haloperidol-induced catalepsy test, revealing its ability to cross the blood-brain barrier. Site-directed mutagenesis and molecular modeling was used to identify the LSP4-2022 binding site, revealing interaction with both the glutamate binding site and a variable pocket responsible for selectivity. These data reveal new approaches for developing selective, hydrophilic, and brain-penetrant mGlu receptor agonists, offering new possibilities to design original bioactive compounds with therapeutic potential.

Several potent and group selective agonists of metabotropic glutamate receptors (mGluRs) have been docked at mGlu1,2,4R binding sites in the closed conformation of the bilobate extracellular domain. Quisqualic acid and (S)-3,5-dihydroxyphenylglycine (3,5-DHPG) were selected for mGlu1R, dicarboxycyclopropylglycine (DCG-IV), LY354740, (S)-4-carboxyphenylglycine (4CPG) for mGlu2R, and (S)-2-amino-4-phosphonobutyric acid (AP4), 1-aminocyclopentane-1,3,4-tricarboxylic acid (ACPT-I), (S)-4-phosphonophenylglycine (PPG) for mGlu4R. The models show a conserved binding pattern for the glycine moiety (alpha-amino and alpha-acidic functions) and group specific bindings for the distal acidic function. The best agonists allow optimized interaction with both lobes of the binding domain. Interlobe connections around the ligand are also described and participate in stabilizing the closed form of the amino-terminal domain. Altogether, the docking models support the proposal that the stabilization of a closed state represents a key step in agonist activation of mGluRs.

A motif for amino acid recognition by proteins or domains of the periplasmic binding

The identification of the chemical structure of an odorant by the vertebrate olfactory system is thought to occur through the combinatorial activity from multiple receptors, each tuned to recognize different chemical features. What are the molecular determinants underlying the selectivity of individual odorant receptors for their cognate ligands? To address this question, we performed molecular modeling and site-directed mutagenesis on the ligand-binding region of two orthologous amino acid odorant receptors belonging to the "C family" of G-protein-coupled receptors in goldfish and zebrafish. We identified the critical ligand-receptor interactions that afford ligand binding as well as selectivity for different amino acids. Moreover, predictions regarding binding pocket structure allowed us to alter, in a predictable manner, the receptor preferences for different ligands. These results reveal how this class of odorant receptor has evolved to accommodate ligands of varying chemical structure and further illuminate the molecular principles underlying ligand recognition and selectivity in this family of chemosensory receptors.

Metabotropic glutamate receptors (mGluRs) play key roles in the modulation of many synapses. Chloride (Cl 2 ) is known to directly bind and regulate the function of different actors of neuronal activity, and several studies have pointed to the possible modulation of mGluRs by Cl 2 . Herein, we demonstrate that Cl 2 behaves as a positive allosteric modulator of mGluRs. For example, whereas glutamate potency was 3.08 6 0.33 mM on metabotropic glutamate (mGlu) 4 receptors in high-Cl 2 buffer, signaling activity was almost abolished in low Cl 2 in cell-based assays.