Chemogenomic discovery of allosteric antagonists at the GPRC6A receptor

GPRC6A is a Family C G protein-coupled receptor recently discovered and deorphanized by our group. This study integrates chemogenomic ligand inference, homology modeling, compound synthesis, and pharmacological mechanism-of-action studies to disclose two noticeable results of methodological and pharmacological character: (1) chemogenomic lead identification through the first, to our knowledge, ligand inference between two different GPCR families, Families A and C; and (2) the discovery of the most selective GPRC6A allosteric antagonists discovered to date. The unprecedented inference of?pharmacological activity across GPCR families provides proof-of-concept for in?silico approaches against Family C targets based on Family A templates, greatly expanding the prospects of successful drug design and discovery. The antagonists were tested against a panel of seven Family A and C G protein-coupled receptors containing the chemogenomic binding sequence motif where some of the identified GPRC6A antagonists showed some activity. However, three compounds with at least ～3-fold selectivity for GPRC6A were discovered, which present a significant step forward compared with the previously published GPRC6A antagonists, calindol and NPS 2143, which both display ～30-fold selectivity for the calcium-sensing receptor compared to GPRC6A. The antagonists constitute novel research tools toward investigating the signaling mechanism of the GPRC6A receptor at the cellular level and serve as initial ligands for further optimization of potency and selectivity enabling future ex?vivo/in?vivo pharmacological studies.     

Parameterization of Org27569: An allosteric modulator of the cannabinoid CB1 G protein‐coupled receptor

The cannabinoid CB₁ receptor is a class A G protein‐coupled receptor (GPCR) that is the most widely expressed GPCR in the brain. Many GPCRs contain allosteric binding sites for endogenous and/or synthetic ligands, which are topographically distinct from the agonist‐binding site that is known as the orthosteric site. While both endogenous and synthetic ligands that act at the CB₁ orthosteric site have been known for some time, compounds that act at a CB₁ allosteric site have only recently been discovered. The most studied of these is 5‐chloro‐3‐ethyl‐1H‐indole‐2‐carboxylic acid [2‐(4‐piperidin‐1‐ylphenyl)ethyl]amide (Org27569). Because allosteric ligands are thought to act through conformational changes in the receptor that are transmitted from the allosteric to the orthosteric site, computational studies of the structural and dynamic interactions of Org27569 with the CB₁ receptor are crucial to achieve a molecular level understanding of the basis of action of this important new class of compounds. To date, such computational studies have not been possible due to the lack of a complete set of molecular mechanics force field parameters for Org27569. Here, we present the development of missing CHARMM force field parameters for Org27569 using previously published methods and the validation and application of these new parameters using normal mode analysis and molecular dynamics simulations combined with experimental infrared measurements. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011     

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.     

High throughput screening of G-protein coupled receptors via flow cytometry

The molecular assemblies of signal transduction components, for example kinases and their target proteins or receptor-ligand complexes and intracellular signaling molecules, are critical for biological functions in cells. To better understand the interactions of these molecular assemblies and to screen for new pharmaceutics that could control and modulate these types of interactions, we have focused on developing high throughput approaches for the analysis of G-protein coupled receptors via flow cytometry. Flow cytometry offers a number of advantages including real-time collection of multicomponent data, and together with improvements in sample handling, the high throughput sampling rate is up to 100 samples per minute. For our targets, assemblies of solubilized GPCRs, a screening platform of a dextran bead has proven to be flexible, allowing different surface chemistries on the beads. The bead can be either ligand-labeled or have epitope-linked proteins attached to the bead surface, enabling several molecular assemblies to be constructed and analyzed. A major improvement with this system is that for screening ligands for GPCRs the underlying mechanism of action for these compounds can be investigated and incorporated into the definition of a 'hit'. Our current screening system is capable of simultaneously distinguishing GPCR agonists and antagonists.     

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.     

Dynamic models of G-protein coupled receptor dimers: indications of asymmetry in the rhodopsin dimer from molecular dynamics simulations in a POPC bilayer

Based on the growing evidence that G-protein coupled receptors (GPCRs) form homo- and hetero-oligomers, models of GPCR signaling are now considering macromolecular assemblies rather than monomers, with the homo-dimer regarded as the minimal oligomeric arrangement required for functional coupling to the G-protein. The dynamic mechanisms of such signaling assemblies are unknown. To gain some insight into properties of GPCR dimers that may be relevant to functional mechanisms, we study their current structural prototype, rhodopsin. We have carried out nanosecond time-scale molecular dynamics (MD) simulations of a rhodopsin dimer and compared the results to the monomer simulated in the same type of bilayer membrane model composed of an equilibrated unit cell of hydrated palmitoyl-oleoyl-phosphatidyl choline (POPC). The dynamic representation of the homo-dimer reveals the location of structural changes in several regions of the monomeric subunits. These changes appear to be more pronounced at the dimerization interface that had been shown to be involved in the activation process [Proc Natl Acad Sci USA 102:17495, 2005]. The results are consistent with a model of GPCR activation that involves allosteric modulation through a single GPCR subunit per dimer.     

Using silico methods predicting ligands for orphan GPCRs

The G-protein coupled receptor (GPCR) superfamily is one of the most important drug target classes for the pharmaceutical industry. The completion of the human genome project has revealed that there are more than 300 potential GPCR targets of interest. The identification of their natural ligands can gain significant insights into regulatory mechanisms of cellular signaling networks and provide unprecedented opportunities for drug discovery. Much effort has been directed towards the GPCR ligand discovery study by both academic institutions and pharmaceutical industries. However, the endogenous ligands still remain unknown for about 150 GPCRs in the human genome. It is necessary to develop new strategies to predict candidate ligands for these so-called orphan receptors. Computational techniques are playing an increasingly important role in finding and validating novel ligands for orphan GPCRs (oGPCRs). In this paper, we focus on recent development in applying bioinformatics approaches for the discovery of GPCR ligands. In addition, some of the data resources for ligand identification are also provided.     

New strategies in drug discovery for GPCRs: high throughput detection of cellular ERK phosphorylation

G-protein coupled receptors (GPCRs) are a large family of receptors for a wide range of stimulants, including hormones, neurotransmitters, and taste and olfactory chemicals. Due to their broad involvement in cellular responses, GPCRs affect many important body functions both in health and disease. Compared to other receptor families, the GPCRs have been a rich source of extracellularly-acting pharmaceuticals, due largely to the fact that many GPCR ligands are small molecules when compared with ligands for other receptors, such as the tyrosine kinase receptor family. This has allowed the development of small molecule modulators of receptor function that act on specific GPCRs, such as those involved in cardiovascular regulation. However, at several levels, current screening technologies of drug development for GPCRs are lacking. Firstly, responses from many GPCRs, such as the Gi-coupled GPCRs, are not easily measured in large screening programs by current techniques. Secondly, there are few options for detecting agonists of orphan GPCRs. Thirdly, it is now clear that the signaling from GPCRs is more complex than once thought, and the measurement of Ca(2+) and cAMP can account for only a fraction of the biological information emanating from an activated GPCR. Studies of the discrete and sometimes separable activation of the Ras/Raf/Mek/ERK cascade by many GPCRs is likely to offer development of new agonists and antagonists, contribute to new pharmacologies from receptors, and raise the potential for novel drug candidates in this important area of biology. Downstream activation of the ERK pathway, with or without transactivation of growth factor receptors, has not been measurable by high throughput methodologies. This article presents recent advances and associated applications for screening of GPCRs and other receptor species through the rapid measurement of protein phosphorylation events, such as ERK phosphorylation, as new readouts for drug discovery.     

Allosteric Optical Control of a Class B G‐Protein‐Coupled Receptor

Allosteric regulation promises to open up new therapeutic avenues by increasing drug specificity at G‐protein‐coupled receptors (GPCRs). However, drug discovery efforts are at present hampered by an inability to precisely control the allosteric site. Herein, we describe the design, synthesis, and testing of PhotoETP, a light‐activated positive allosteric modulator of the glucagon‐like peptide‐1 receptor (GLP‐1R), a class B GPCR involved in the maintenance of glucose homeostasis in humans. PhotoETP potentiates Ca²⁺, cAMP, and insulin responses to glucagon‐like peptide‐1 and its metabolites following illumination of cells with blue light. PhotoETP thus provides a blueprint for the production of small‐molecule class B GPCR allosteric photoswitches, and may represent a useful tool for understanding positive cooperativity at the GLP‐1R.     

Photoswitching the Efficacy of a Small‐Molecule Ligand for a Peptidergic GPCR: from Antagonism to Agonism

For optical control of GPCR function, we set out to develop small‐molecule ligands with photoswitchable efficacy in which both configurations bind the target protein but exert distinct pharmacological effects, that is, stimulate or antagonize GPCR activation. Our design was based on a previously identified efficacy hotspot for the peptidergic chemokine receptor CXCR3 and resulted in the synthesis and characterization of five new azobenzene‐containing CXCR3 ligands. G protein activation assays and real‐time electrophysiology experiments demonstrated photoswitching from antagonism to partial agonism and even to full agonism (compound VUF16216). SAR evaluation suggests that the size and electron‐donating properties of the substituents on the inner aromatic ring are important for the efficacy photoswitching. These compounds are the first GPCR azo ligands with a nearly full efficacy photoswitch and may become valuable pharmacological tools for the optical control of peptidergic GPCR signaling.     

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.     

Could the presence of sodium ion influence the accuracy and precision of the ligand-posing in the human A<Subscript>2A</Subscript> adenosine receptor orthosteric binding site using a molecular docking approach? Insights from <Emphasis Type="Italic">Dockbench</Emphasis>

The allosteric modulation of G protein-coupled receptors (GPCRs) by sodium ions has received considerable attention as crystal structures of several receptors, in their inactive conformation, show a Na⁺ ion bound to specific residues which, in the human A_2A adenosine receptor (hA_2A AR), are Ser91^3.39, Trp246^6.48, Asn280^7.45, and Asn284^7.49. A cluster of water molecules completes the coordination of the sodium ion in the putative allosteric site. It is absolutely consolidated that the progress made in the field of GPCRs structural determination has increased the adoption of docking-driven approaches for the identification or the optimization of novel potent and selective ligands. Despite the extensive use of docking protocols in virtual screening approaches, to date, almost any of these studies have been carried out without taking into account the presence of the sodium cation and its first solvation shell in the putative allosteric binding site. In this study, we have focused our attention on determining how the presence of sodium ion binding and additionally its first hydration sphere, in hA_2AAR could influence the ligand positioning accuracy during molecular docking simulations for most of the available resting and activated hA_2A AR crystal structures, using DockBench as a comparative benchmarking tool and implementing a new correlation coefficient (EM). This work provides indications on the evidence that the posing performance (accuracy and/or precision) of the docking protocols in reproducing the crystallographic poses of different hA_2A AR antagonists is generally increased in the presence of the sodium cation and its first solvation shell, in agreement with experimental observations. Consequently, the inclusion of sodium ion and its first solvation shell should be considered in order to facilitate the selection of new potential ligands in all molecular docking-based virtual screening protocols that aim to find novel GPCRs antagonists and inverse agonists.     

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.     

Identification and characterization of mGlu3 ligands using a high throughput FLIPR assay for detection of agonists, antagonists, and allosteric modulators

When targeting G-protein coupled receptors (GPCRs) in early stage drug discovery, or for novel targets, the type of ligand most likely to produce the desired therapeutic effect may be unknown. Therefore, it can be desirable to identify potential lead compounds from multiple categories: agonists, antagonists, and allosteric modulators. In this study, we developed a triple addition calcium flux assay using FLIPR Tetra to identify multiple ligand classes for the metabotropic glutamate receptor 3 (mGlu3), using a cell line stably co-expressing the human G-protein-coupled mGlu3 receptor, a promiscuous G-protein (G(α16)), and rat Glast, a glutamate transporter. Compounds were added to the cells followed by stimulation with EC(10) and then EC(80) concentration of glutamate, the physiological agonist for mGlu receptors. This format produced a robust assay, facilitating the identification of agonists, positive allosteric modulators and antagonists/negative allosteric modulators. Follow up experiments were conducted to exclude false positives. Using this approach, we screened a library of approximately 800,000 compounds using FLIPR Tetra and identified viable leads for all three ligand classes. Further characterization revealed the selectivity of individual ligands.     

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.     

A virtual screen for diverse ligands: discovery of selective G protein-coupled receptor antagonists

Virtual screening has become a major focus of bioactive small molecule lead identification, and reports of agonists and antagonists discovered via virtual methods are becoming more frequent. G protein-coupled receptors (GPCRs) are the one class of protein targets for which success with this approach has been limited. This is likely due to the paucity of detailed experimental information describing GPCR structure and the intrinsic function-associated structural flexibility of GPCRs which present major challenges in the application of receptor-based virtual screening. Here we describe an in silico methodology that diminishes the effects of structural uncertainty, allowing for more inclusive representation of a potential docking interaction with exogenous ligands. Using this approach, we screened one million compounds from a virtual database, and a diverse subgroup of 100 compounds was selected, leading to experimental identification of five structurally diverse antagonists of the thyrotropin-releasing hormone receptors (TRH-R1 and TRH-R2). The chirality of the most potent chemotype was demonstrated to be important in its binding affinity to TRH receptors; the most potent stereoisomer was noted to have a 13-fold selectivity for TRH-R1 over TRH-R2. A comprehensive mutational analysis of key amino acid residues that form the putative binding pocket of TRH receptors further verified the binding modality of these small molecule antagonists. The described virtual screening approach may prove applicable in the search for novel small molecule agonists and antagonists of other GPCRs.     

High content screening for G protein-coupled receptors using cell-based protein translocation assays

G protein-coupled receptors (GPCRs) have been one of the most productive classes of drug targets for several decades, and new technologies for GPCR-based discovery promise to keep this field active for years to come. While molecular screens for GPCR receptor agonist- and antagonist-based drugs will continue to be valuable discovery tools, the most exciting developments in the field involve cell-based assays for GPCR function. Some cell-based discovery strategies, such as the use of beta-arrestin as a surrogate marker for GPCR function, have already been reduced to practice, and have been used as valuable discovery tools for several years. The application of high content cell-based screening to GPCR discovery has opened up additional possibilities, such as direct tracking of GPCRs, G proteins and other signaling pathway components using intracellular translocation assays. These assays provide the capability to probe GPCR function at the cellular level with better resolution than has previously been possible, and offer practical strategies for more definitive selectivity evaluation and counter-screening in the early stages of drug discovery. The potential of cell-based translocation assays for GPCR discovery is described, and proof-of-concept data from a pilot screen with a CXCR4 assay are presented. This chemokine receptor is a highly relevant drug target which plays an important role in the pathogenesis of inflammatory disease and also has been shown to be a co-receptor for entry of HIV into cells as well as to play a role in metastasis of certain cancer cells.     

GPCR structure-based virtual screening approach for CB2 antagonist search

The potential for therapeutic specificity in regulating diseases has made cannabinoid (CB) receptors one of the most important G-protein-coupled receptor (GPCR) targets in search for new drugs. Considering the lack of related 3D experimental structures, we have established a structure-based virtual screening protocol to search for CB2 bioactive antagonists based on the 3D CB2 homology structure model. However, the existing homology-predicted 3D models often deviate from the native structure and therefore may incorrectly bias the in silico design. To overcome this problem, we have developed a 3D testing database query algorithm to examine the constructed 3D CB2 receptor structure model as well as the predicted binding pocket. In the present study, an antagonist-bound CB2 receptor complex model was initially generated using flexible docking simulation and then further optimized by molecular dynamic and mechanical (MD/MM) calculations. The refined 3D structural model of the CB2-ligand complex was then inspected by exploring the interactions between the receptor and ligands in order to predict the potential CB2 binding pocket for its antagonist. The ligand-receptor complex model and the predicted antagonist binding pockets were further processed and validated by FlexX-Pharm docking against a testing compound database that contains known antagonists. Furthermore, a consensus scoring (CScore) function algorithm was established to rank the binding interaction modes of a ligand on the CB2 receptor. Our results indicated that the known antagonists seeded in the testing database can be distinguished from a significant amount of randomly chosen molecules. Our studies demonstrated that the established GPCR structure-based virtual screening approach provided a new strategy with a high potential for in silico identifying novel CB2 antagonist leads based on the homology-generated 3D CB2 structure model.     

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.