An automated system for the analysis of G protein-coupled receptor transmembrane binding pockets: alignment, receptor-based pharmacophores, and their application

G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Here, a comprehensive and automated method allowing fast analysis and comparison of these putative binding pockets across the entire GPCR family is presented. The method relies on a robust alignment algorithm based on conservation indices, focusing on pharmacophore-like relationships between amino acids. Analysis of conservation patterns across the GPCR family and alignment to the rhodopsin X-ray structure allows the extraction of the amino acids lining the TM binding pocket in a so-called ligand binding pocket vector (LPV). In a second step, LPVs are translated to simple 3D receptor pharmacophore models, where each amino acid is represented by a single spherical pharmacophore feature and all atomic detail is omitted. Applications of the method include the assessment of selectivity issues, support of mutagenesis studies, and the derivation of rules for focused screening to identify chemical starting points in early drug discovery projects. Because of the coarseness of this 3D receptor pharmacophore model, however, meaningful scoring and ranking procedures of large sets of molecules are not justified. The LPV analysis of the trace amine-associated receptor family and its experimental validation is discussed as an example. The value of the 3D receptor model is demonstrated for a class C GPCR family, the metabotropic glutamate receptors.     

CB1 Cannabinoid Receptor Signaling and Biased Signaling

The CB1 cannabinoid receptor is a G-protein coupled receptor highly expressed throughout the central nervous system that is a promising target for the treatment of various disorders, including anxiety, pain, and neurodegeneration. Despite the wide therapeutic potential of CB1, the development of drug candidates is hindered by adverse effects, rapid tolerance development, and abuse potential. Ligands that produce biased signaling—the preferential activation of a signaling transducer in detriment of another—have been proposed as a strategy to dissociate therapeutic and adverse effects for a variety of G-protein coupled receptors. However, biased signaling at the CB1 receptor is poorly understood due to a lack of strongly biased agonists. Here, we review studies that have investigated the biased signaling profile of classical cannabinoid agonists and allosteric ligands, searching for a potential therapeutic advantage of CB1 biased signaling in different pathological states. Agonist and antagonist bound structures of CB1 and proposed mechanisms of action of biased allosteric modulators are used to discuss a putative molecular mechanism for CB1 receptor activation and biased signaling. Current studies suggest that allosteric binding sites on CB1 can be explored to yield biased ligands that favor or hinder conformational changes important for biased signaling.     

Engineered chimeric enzymes as tools for drug discovery: generating reliable bacterial screens for the detection, discovery, and assessment of estrogen receptor modulators

Engineered protein-based sensors of ligand binding have emerged as attractive tools for the discovery of therapeutic compounds through simple screening systems. We have previously shown that engineered chimeric enzymes, which combine the ligand-binding domains of nuclear hormone receptors with a highly sensitive thymidylate synthase reporter, yield simple sensors that report the presence of hormone-like compounds through changes in bacterial growth. This work describes an optimized estrogen sensor in Escherichia coli with extraordinary reliability in identifying diverse estrogenic compounds and in differentiating between their agonistic/antagonistic pharmacological effects. The ability of this system to assist the discovery of new estrogen-mimicking compounds was validated by screening a small compound library, which led to the identification of two structurally novel estrogen receptor modulators and the accurate prediction of their agonistic/antagonistic biocharacter in human cells. Strong evidence is presented here that the ability of our sensor to detect ligand binding and recognize pharmacologically critical properties arises from allosteric communication between the artificially combined protein domains, where different ligand-induced conformational changes in the receptor are transmitted to the catalytic domain and translated to distinct levels of enzymic efficiency. To the best of our knowledge, this is one of the first examples of an engineered enzyme with the ability to sense multiple receptor conformations and to be either activated or inactivated depending on the nature of the bound effector molecule. Because the proposed mechanism of ligand dependence is not specific to nuclear hormone receptors, we anticipate that our protein engineering strategy will be applicable to the construction of simple sensors for different classes of (therapeutic) binding proteins.     

Allosteric antagonist binding sites in class B GPCRs: corticotropin receptor 1

The 41 amino acid neuropeptide, corticotropin-releasing factor (CRF) and its associated receptors CRF₁-R and CRF₂-R have been targeted for treating stress related disorders. Both CRF₁-R and CRF₂-R belong to the class B G-protein coupled receptors for which little information is known regarding the small molecule antagonist binding characteristics. However, it has been shown recently that different non-peptide allosteric ligands stabilize different receptor conformations for CRF₁-R and hence an understanding of the ligand induced receptor conformational changes is important in the pharmacology of ligand binding. In this study, we modeled the receptor and identified the binding sites of representative small molecule allosteric antagonists for CRF₁-R. The predicted binding sites of the investigated compounds are located within the transmembrane (TM) domain encompassing TM helices 3, 5 and 6. The docked compounds show strong interactions with H228 on TM3 and M305 on TM5 that have also been implicated in the binding by site directed mutation studies. H228 forms a hydrogen bond of varied strengths with all the antagonists in this study and this is in agreement with the decreased binding affinity of several compounds with H228F mutation. Also mutating M305 to Ile showed a sharp decrease in the calculated binding energy whereas the binding energy loss on M305 to Leu was less significant. These results are in qualitative agreement with the decrease in binding affinities observed experimentally. We further predicted the conformational changes in CRF₁-R induced by the allosteric antagonist NBI-27914. Movement of TM helices 3 and 5 are dominant and generates three degenerate conformational states two of which are separated by an energy barrier from the third, when bound to NBI-27914. Binding of NBI-27914 was predicted to improve the interaction of the ligand with M305 and also enhanced the aromatic stacking between the ligand and F232 on TM3. A virtual ligand screening of ~13,000 compounds seeded with ~350 CRF₁-R specific active antagonists performed on the NBI-27914 stabilized conformation of CRF₁-R yielded a 44% increase in enrichment compared to the initially modeled receptor conformation at a 10% cutoff. The NBI-27914 stabilized conformation also shows a high enrichment for high affinity antagonists compared to the weaker ones. Thus, the conformational changes induced by NBI-27914 improved the ligand screening efficiency of the CRF₁-R model and demonstrate a generalized application of the method in drug discovery.     

A general technique to rank protein-ligand binding affinities and determine allosteric versus direct binding site competition in compound mixtures

To realize the full potential of combinatorial chemistry-based drug discovery, generic and efficient tools must be developed that apply the strengths of diversity-oriented chemical synthesis to the identification and optimization of lead compounds for disease-associated protein targets. We report an affinity selection-mass spectrometry (AS-MS) method for protein-ligand affinity ranking and the classification of ligands by binding site. The method incorporates the following steps: (1) an affinity selection stage, where protein-binding compounds are selected from pools of ligands in the presence of varying concentrations of a competitor ligand, (2) a first chromatography stage to separate unbound ligands from protein-ligand complexes, and (3) a second chromatography stage to dissociate the ligands from the complexes for identification and quantification by MS. The ability of the competitor ligand to displace a target-bound library member, as measured by MS, reveals the binding site classification and affinity ranking of the mixture components. The technique requires no radiolabel incorporation or direct biochemical assay, no modification or immobilization of the compounds or target protein, and all reaction components, including any buffers or cofactors required for protein stability, are free in solution. We demonstrate the method for several compounds of wide structural variety against representatives of the most important protein classes in contemporary drug discovery, including novel ATP-competitive and allosteric inhibitors of the Akt-1 (PKB) and Zap-70 kinases, and previously undisclosed antagonists of the M(2) muscarinic acetylcholine receptor, a G-protein coupled receptor (GPCR). The theoretical basis of the technique is analyzed mathematically, allowing quantitative estimation of binding affinities and, in the case of allosteric interaction, absolute determination of binding cooperativity. The method is readily applicable to high-throughput screening hit triage, combinatorial library-based affinity optimization, and developing structure-activity relationships among multiple ligands to a given receptor.     

Functional characterisation of homomeric ionotropic glutamate receptors GluR1-GluR6 in a fluorescence-based high throughput screening assay

We have constructed stable HEK293 cell lines expressing the rat ionotropic glutamate receptor subtypes GluR1(i), GluR2Q(i), GluR3(i), GluR4(i), GluR5Q and GluR6Q and characterised the pharmacological profiles of the six homomeric receptors in a fluorescence-based high throughput screening assay using Fluo-4/AM as a fluorescent Ca2+ indicator. In this assay, the pharmacological properties of nine standard GluR ligands correlated nicely with those previously observed in electrophysiology studies of GluRs expressed in Xenopus oocytes or mammalian cells. The potencies and efficacies displayed by the agonists (S)-glutamate, (S)-quisqualate, kainate, (RS)-AMPA, (RS)-ATPA, (RS)-ACPA] and (S)-4-AHCP at the six GluRs were in concordance with electrophysiological studies. Furthermore, the Ki values exhibited by the competitive antagonists NBQX and (RS)-ATPO were also in agreement with findings of previous studies. Finally, the effects of various concentrations of Ca2+ in the assay buffer and of the allosteric modulators cyclothiazide and concanavalin A on GluR signalling were examined. This study represents the most elaborate functional characterisation of multiple AMPA and KA receptor subtypes in the same assay reported to date. We propose that high throughput screening of compound libraries at the six GluR-HEK293 cell lines could be helpful in the search for structurally and pharmacologically novel ligands acting at the receptors.     

Virtual screening of organic molecule databases. Design of focused libraries of potential ligands of NMDA and AMPA receptors

A system of virtual screening of organic molecule databases is designed, which permits preprocessing of databases, molecular docking to a three-dimensional model of receptor, and post-processing of the results obtained. Using this screening system, it is possible to reproduce positions of the known ligands in the glutamate sites of the NMDA and AMPA receptors and in the glycine site of the NMDA receptor, to substantially enrich the database with potentially active compounds, and to distinguish between the agonistic and antagonistic character of the action of these compounds in the case of docking to the open and closed forms of the binding sites. Based on the results of screening of a database of low-molecular-weight organic compounds (total of 135,000 structures) using models of the open and closed forms of the glutamate and glycine sites of the NMDA receptor and of the glutamate site of the AMPA receptor, focused libraries of potential agonists and antagonists of these sites were designed.     

A combination of flow and batch mode processes for the efficient preparation of mGlu2/3 receptor negative allosteric modulators (NAMs)

Benzodiazepinones are privileged scaffolds with activity against multiple therapeutically relevant biological targets. In support of our ongoing studies around allosteric modulators of metabotropic glutamate receptors (mGlus) we required the multigram synthesis of a β-ketoester key intermediate. We report the continuous flow synthesis of tert-butyl 3-(2-cyanopyridin-4-yl)-3-oxopropanoate and its transformation to potent mGlu_2/3 negative allosteric modulators (NAMs) in batch mode.     

Multiple Binding Sites Contribute to the Mechanism of Mixed Agonistic and Positive Allosteric Modulators of the Cannabinoid CB1 Receptor

The cannabinoid CB1 receptor (CB1R) is an abundant metabotropic G‐protein‐coupled receptor that has been difficult to address therapeutically because of CNS side effects exerted by orthosteric drug candidates. Recent efforts have focused on developing allosteric modulators that target CB1R. Compounds from the recently discovered class of mixed agonistic and positive allosteric modulators (Ago‐PAMs) based on 2‐phenylindoles have shown promising functional and binding properties as CB1R ligands. Here, we identify binding modes of both the CP 55,940 agonist and GAT228, a 2‐phenylindole allosteric modulator, by using our metadynamics simulation protocol, and quantify their affinity and cooperativity by atomistic simulations. We demonstrate the involvement of multiple adjunct binding sites in the Ago‐PAM characteristics of the 2‐phenylindole modulators and explain their ability to compete with orthosteric agonists at higher concentrations. We validate these results experimentally by showing the contribution of multiple sites on the allosteric binding of ZCZ011, another homologous member of the class, together with the orthosteric agonist.     

Synthesis and biological activities of conformationally restricted cyclopentenyl-glutamate analogues.

An efficient method for preparing conformationally restricted cyclopentenyl-glutamate analogues in a regioselective and diastereoselective manner has been developed using a formal [3 + 2] cycloaddition reaction of dehydroamino acids. Methods for preparing optically active versions of these compounds have also been devised. Of these compounds, (S)-2 is an agonist at the mGlu5 (EC(50) 18 microM) and mGlu2 (EC(50) 45 microM) receptors.     

Identification of Two Distinct Sites for Antagonist and Biased Agonist Binding to the Human Chemokine Receptor CXCR3

The chemokine receptor CXCR3 is a G protein‐coupled receptor that conveys extracellular signals into cells by changing its conformation upon ligand binding. We previously hypothesized that small‐molecule allosteric CXCR3‐agonists do not bind to the same allosteric binding pocket as 8‐azaquinazolinone‐based negative allosteric modulators. We have now performed molecular‐dynamics (MD) simulations with metadynamics enhanced sampling on the CXCR3 system to refine structures and binding modes and to predict the CXCR3‐binding affinities of the biased allosteric agonist FAUC1036 and the negative allosteric modulator RAMX3. We have identified two distinct binding sites; a “shallow” and a second “deeper” pocket to which the biased allosteric agonist FAUC1036 and negative allosteric modulator RAMX3 bind, respectively.     

Prediction of the 3D structure and dynamics of human DP G-protein coupled receptor bound to an agonist and an antagonist

Prostanoids play important physiological roles in the cardiovascular and immune systems and in pain sensation in peripheral systems through their interactions with eight G-protein coupled receptors. These receptors are important drug targets, but development of subtype specific agonists and antagonists has been hampered by the lack of 3D structures for these receptors. We report here the 3D structure for the human DP G-protein coupled receptor (GPCR) predicted by the MembStruk computational method. To validate this structure, we use the HierDock computational method to predict the binding mode for the endogenous agonist (PGD2) to DP. Based on our structure, we predicted the binding of different antagonists and optimized them. We find that PGD2 binds vertically to DP in the TM1237 region with the alpha chain toward the extracellular (EC) region and the omega chain toward the middle of the membrane. This structure explains the selectivity of the DP receptor and the residues involved in the predicted binding site correlate very well with available mutation experiments on DP, IP, TP, FP, and EP subtypes. We report molecular dynamics of DP in explicit lipid and water and find that the binding of the PGD2 agonist leads to correlated rotations of helices of TM3 and TM7, whereas binding of antagonist leads to no such rotations. Thus, these motions may be related to the mechanism of activation.     

Development of selective high affinity antagonists, agonists, and radioligands for the P2Y1 receptor

The P2Y(1) receptor is a member of the P2Y family of nucleotide-activated G protein-coupled receptors, and it is an important therapeutic target based on its broad tissue distribution and essential role in platelet aggregation. We have designed a set of highly selective and diverse pharmacological tools for studying the P2Y(1) receptor using a rational approach to ligand design. Based on the discovery that bisphosphate analogues of the P2Y(1) receptor agonist, ADP, are partial agonists/competitive antagonists of this receptor, an iterative approach was used to develop competitive antagonists with enhanced affinity and selectivity. Halogen substitutions of the 2-position of the adenine ring provided increased affinity while an N(6) methyl substitution eliminated partial agonist activity. Furthermore, various replacements of the ribose ring with symmetrically branched, phosphorylated acyclic structures revealed that the ribose is not necessary for recognition at the P2Y(1) receptor. Finally, replacement of the ribose ring with a five member methanocarba ring constrained in the Northern conformation conferred dramatic increases in affinity to both P2Y(1) receptor antagonists as well as agonists. These combined structural modifications have resulted in a series of selective high affinity antagonists of the P2Y(1) receptor, two broadly applicable radioligands, and a high affinity agonist capable of selectively activating the P2Y(1) receptor in human platelets. Complementary receptor modeling and computational ligand docking have provided a putative structural framework for the drug-receptor interactions. A similar rational approach is being applied to develop selective ligands for other subtypes of P2Y receptors.     

Different binding modes of structurally diverse ligands for human D3DAR

Five different dopamine D3 receptors (D3DARs) models were created considering some suggested binding modes for D3DAR antagonists reported in earlier computational studies. Different hypotheses are justified because of the lack of experimental information about the putative site of interaction and are also due to the variability in scaffolds and size of D3DAR ligands. In this study 114 potent and selective D3DAR antagonists or partial agonists are used as key experimental information to discriminate the most reliable receptor model and to build a docking based 3D quantitative structure-activity relationship model able to indicate the ligand properties and the residues important for activity. The ability of this D3DAR model to discriminate the binding mode of different classes of ligands, showing a good quantitative correlation with their activity, encourages us to use it for screening novel lead compounds.     

Homology model-based virtual screening for GPCR ligands using docking and target-biased scoring

The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS). Our approach was evaluated in retrospective virtual screening experiments for antagonists of the metabotropic glutamate receptor (mGluR) subtype 5. The results of our approach were compared to the results obtained by conventional scoring functions (Dock-Score, PMF-Score, Gold-Score, ChemScore, and FlexX-Score). The IFS lead to significantly higher enrichment rates, relative to the competing scoring functions. Though using a target-biased scoring approach, the results were not biased toward the chemical classes of the reference structures. Our results indicate that the presented approach has the potential to serve as a general setup for successful structure-based GPCR virtual screening.     

Azetidinic amino acids: stereocontrolled synthesis and pharmacological characterization as ligands for glutamate receptors and transporters

A set of ten azetidinic amino acids, that can be envisioned as C-4 alkyl substituted analogues of trans-2-carboxyazetidine-3-acetic acid (t-CAA) and/or conformationally constrained analogues of (R)- or (S)-glutamic acid (Glu) have been synthesized in a diastereo- and enantiomerically pure form from beta-amino alcohols through a straightforward five step sequence. The key step of this synthesis is an original anionic 4-exo-tet ring closure that forms the azetidine ring upon an intramolecular Michael addition. This reaction was proven to be reversible and to lead to a thermodynamic distribution of two diastereoisomers that were easily separated and converted in two steps into azetidinic amino acids. Azetidines 35-44 were characterized in binding studies on native ionotropic Glu receptors and in functional assays at cloned metabotropic receptors mGluR1, 2 and 4, representing group I, II and III mGlu receptors, respectively. Furthermore, azetidine analogues 35, 36, and 40 were also characterized as potential ligands at the glutamate transporter subtypes EAAT1-3 in the FLIPR Membrane Potential (FMP) assay. The (2R)-azetidines 35, 37, 39, 41 and 43 were inactive in iGlu, mGlu and EAAT assays, whereas a marked change in the pharmacological profile at the iGlu receptors was observed when a methyl group was introduced in the C-4 position, compound 36 versus t-CAA. At EAAT1-3, compound 35 was inactive, whereas azetidines 36 and 40 were both identified as inhibitors and showed selectivity for the EAAT2 subtype.     

Molecular Alliance—From Orthosteric and Allosteric Ligands to Dualsteric/Bitopic Agonists at G Protein Coupled Receptors

Cell‐membrane‐spanning G protein coupled receptors (GPCRs) belong to the most important therapeutic target structures. Endogenous transmitters bind from the outer side of the membrane to the “orthosteric” binding site either deep in the binding pocket or at the extracellular N‐terminal end of the receptor protein. Exogenous modulators that utilize a different, “allosteric”, binding site unveil a pathway to receptor subtype‐selectivity. However, receptor activation through the orthosteric area is often more powerful. Recently there has been evidence that orthosteric/allosteric, in other words “dualsteric”, hybrid compounds unite subtype selectivity and receptor activation. These “bitopic” modulators channelreceptor activation and subsequent intracellular signaling into a subset of possible routes. This concept offers access to GPCR modulators with an unprecedented receptor‐subtype and signaling selectivity profile and, as a consequence, to drugs with fewer side effects.     

Functional selectivity in GPCR modulator screening

In high throughput screening systems, a single concentration of a new compound is tested in a biological system to detect direct effects (agonists) or effects on other ligands (antagonists). In this latter case, the chemical context of the assay is defined by a balance of maximal sensitivity (limited agonist concentration) and maximal window to observe effect (sizable agonist concentration to induce measurable effect). For allosteric modulators, there are other factors that should be considered in high throughput screening environments. Specifically, the saturable aspect of allosteric effect can dissociate the observed ordinate change in response (% inhibition) and potency of effect (concentration at which a given ordinate % effect is obtained). Also, the specter of probe dependence can be important in systems where the physiologically relevant agonist cannot be used for screening (i.e. HIV-1 entry). Finally, the interactive nature of allosteric systems can cause complex relationships between the chemical context of an assay and potency of allosteric modulator. For example, in cases where the efficacy of an agonist is reduced but the affinity is increased by a modulator, it may be more beneficial to have higher concentrations of agonist in the screening assay to optimize sensitivity to modulators. This must be balanced for allosteric potentiators with the need to retain a window to observe increased agonist effect.     

Three-dimensional models of glutamate receptors

Structural models of glutamate receptors have been produced as part of a multidisciplinary study of neuronal function--both ligand/receptor interactions and ion transport--at the atomic level. The models have concentrated on the agonist binding and transmembrane domains of ionotropic (i.e. ligand-gated) glutamate receptors (iGluRs), and have aided our understanding of the molecular determinants of (1) ligand binding and (2) channel activity. The model building process involved a combination of homology modelling, distance geometry, molecular mechanics, protein-ligand and protein-protein docking, electrostatic calculations and manual adjustment, in conjunction with restraints from site-directed mutagenesis, ligand binding and electrophysiological studies. The initial models were used to produce hypotheses which were tested experimentally; these models have been subsequently refined as part of an extremely effective multidisciplinary study using an iterative molecular modelling/experimental verification cycle in which restraints derived from experimental studies are used at all stages, and the findings from one round of modelling are used as restraints in the next. By studying a variety of agonists and antagonists, details have been built up of (1) those residues involved in ligand binding and (2) the role of agonist binding (i.e. agonist-induced conformational change) in channel gating. The models also aid our understanding of the conductance properties of the channels.