Discovery of a Positive Allosteric Modulator of Cholecystokinin Action at CCK1R in Normal and Elevated Cholesterol.

Drugs useful in prevention/treatment of obesity could improve health. Cholecystokinin (CCK) is a key regulator of appetite, working through the type 1 CCK receptor (CCK1R); however, full agonists have not stimulated more weight loss than dieting. We proposed an alternate strategy to target this receptor, while reducing likelihood of side effects and/or toxicity. Positive allosteric modulators (PAMs) with minimal intrinsic agonist activity would enhance CCK action, while maintaining spatial and temporal characteristics of physiologic signaling. This could correct abnormal stimulus-activity coupling observed in a high-cholesterol environment observed in obesity. We utilized high-throughput screening to identify a molecule with this pharmacological profile and studied its basis of action. Compound 1 was a weak partial agonist, with PAM activity to enhance CCK action at CCK1R, but not CCK2R, maintained in both normal and high cholesterol. Compound 1 (10 µM) did not exhibit agonist activity or stimulate internalization of CCK1R. It enhanced CCK activity by slowing the off-rate of bound hormone, increasing its binding affinity. Computational docking of Compound 1 to CCK1R yielded plausible poses. A radioiodinatable photolabile analogue retained Compound 1 pharmacology and covalently labeled CCK1R Thr211, consistent with one proposed pose. Our study identifies a novel, selective, CCK1R PAM that binds to the receptor to enhance action of CCK-8 and CCK-58 in both normal and disease-mimicking high-cholesterol environments. This facilitates the development of compounds that target the physiologic spatial and temporal engagement of CCK1R by CCK that underpins its critical role in metabolic regulation.

Two distinct domains of the glucagon-like peptide-1 receptor control peptide-mediated biased agonism.

G protein-coupled receptors (GPCRs) can be differentially activated by ligands to generate multiple and distinct downstream signaling profiles, a phenomenon termed biased agonism. The glucagon-like peptide-1 receptor (GLP-1R) is a class B GPCR and a key drug target for managing metabolic disorders; however, its peptide agonists display biased signaling that affects their relative efficacies. In this study, we combined mutagenesis experiments and mapping of surface mutations onto recently described GLP-1R structures, which revealed two major domains in the GLP-1/GLP-1R/Gs protein active structure that are differentially important for both receptor quiescence and ligand-specific initiation and propagation of biased agonism. Changes to the conformation of transmembrane helix (TM) 5 and TM 6 and reordering of extracellular loop 2 were essential for the propagation of signaling linked to cAMP formation and intracellular calcium mobilization, whereas ordering and packing of residues in TMs 1 and 7 were critical for extracellular signal-regulated kinase 1/2 (pERK) activity. On the basis of these findings, we propose a model of distinct peptide-receptor interactions that selectively control how these different signaling pathways are engaged. This work provides important structural insight into class B GPCR activation and biased agonism.

Improving virtual screening of G protein-coupled receptors via ligand-directed modeling.

G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state.

Phase-plate cryo-EM structure of a class B GPCR-G-protein complex.

Class B G-protein-coupled receptors are major targets for the treatment of chronic diseases, such as osteoporosis, diabetes and obesity. Here we report the structure of a full-length class B receptor, the calcitonin receptor, in complex with peptide ligand and heterotrimeric Gαsßγ protein determined by Volta phase-plate single-particle cryo-electron microscopy. The peptide agonist engages the receptor by binding to an extended hydrophobic pocket facilitated by the large outward movement of the extracellular ends of transmembrane helices 6 and 7. This conformation is accompanied by a 60° kink in helix 6 and a large outward movement of the intracellular end of this helix, opening the bundle to accommodate interactions with the α5-helix of Gαs. Also observed is an extended intracellular helix 8 that contributes to both receptor stability and functional G-protein coupling via an interaction with the Gß subunit. This structure provides a new framework for understanding G-protein-coupled receptor function.

Structural features embedded in G protein-coupled receptor co-crystal structures are key to their success in virtual screening.

Structure based drug discovery on GPCRs harness atomic detail X-ray binding pockets and large libraries of potential drug lead candidates in virtual screening (VS) to identify novel lead candidates. Relatively small conformational differences between such binding pockets can be critical to the success of VS. Retrospective VS on GPCR/ligand co-crystal structures revealed stark differences in the ability of different structures to identify known ligands, despite being co-crystallized with the same ligand. When using the OpenEye toolkit and the ICM modeling package, we identify criteria associated with the predictive power of binding pockets in VS that consists of a combination of ligand/receptor interaction pattern and predicted ligand/receptor interaction strength. These findings can guide the selection and refinement of GPCR binding pockets for use in SBDD programs and may also provide a potential framework for evaluating the ability of computational GPCR binding pocket refinement tools in improving the predictive power of binding pockets.

Systematic analysis of factors influencing observations of biased agonism at the mu-opioid receptor.

Biased agonism describes the ability of distinct G protein-coupled receptor (GPCR) ligands to stabilise distinct receptor conformations leading to the activation of different cell signalling pathways that can deliver different physiologic outcomes. This phenomenon is having a major impact on modern drug discovery as it offers the potential to design ligands that selectively activate or inhibit the signalling pathways linked to therapeutic effects with minimal activation or blockade of signalling pathways that are linked to the development of adverse on-target effects. However, the explosion in studies of biased agonism at multiple GPCR families in recombinant cell lines has revealed a high degree of variability on descriptions of biased ligands at the same GPCR and raised the question of whether biased agonism is a fixed attribute of a ligand in all cell types. The current study addresses this question at the mu-opioid receptor (MOP). Here, we have systematically assessed the impact of differential cellular protein complement (and cellular background), signalling kinetics and receptor species on our previous descriptions of biased agonism at MOP by several opioid peptides and synthetic opioids. Our results show that all these factors need to be carefully determined and reported when considering biased agonism. Nevertheless, our studies also show that, despite changes in overall signalling profiles, ligands that previously showed distinct bias profiles at MOP retained their uniqueness across different cell backgrounds.

Prediction of Loops in G Protein-Coupled Receptor Homology Models: Effect of Imprecise Surroundings and Constraints.

In the present study, we explored the extent to which inaccuracies inherent in homology models of the transmembrane helical cores of G protein-coupled receptors (GPCRs) can impact loop prediction. We demonstrate that loop prediction in homology models is much more difficult than loop reconstruction in crystal structures because of the imprecise positioning of loop anchors. Deriving information from 17 recently available GPCR crystal structures, we estimated all of the possible errors that could occur in loop anchors as the result of comparative modeling. Subsequently, we performed an exhaustive analysis to decipher the effect of these errors on loop modeling using ICM High Precision Sampling. The influence of the presence of other extracellular loops was also explored. Our results reveal that the error space of modeled loop residues is much larger than that of the anchor residues, although modeling a particular extracellular loop in the presence of other extracellular loops provides constraints that help in predicting near-native loop conformations observed in crystal structures. This implies that errors in loop anchor positions introduce increased uncertainty in the modeled loop coordinates. Therefore, for the success of any GPCR structure prediction algorithm, minimizing errors in the helical end points is likely to be critical for successful loop modeling.

The role of kinetic context in apparent biased agonism at GPCRs.

Biased agonism describes the ability of ligands to stabilize different conformations of a GPCR linked to distinct functional outcomes and offers the prospect of designing pathway-specific drugs that avoid on-target side effects. This mechanism is usually inferred from pharmacological data with the assumption that the confounding influences of observational (that is, assay dependent) and system (that is, cell background dependent) bias are excluded by experimental design and analysis. Here we reveal that 'kinetic context', as determined by ligand-binding kinetics and the temporal pattern of receptor-signalling processes, can have a profound influence on the apparent bias of a series of agonists for the dopamine D2 receptor and can even lead to reversals in the direction of bias. We propose that kinetic context must be acknowledged in the design and interpretation of studies of biased agonism.

A Hydrogen-Bonded Polar Network in the Core of the Glucagon-Like Peptide-1 Receptor Is a Fulcrum for Biased Agonism: Lessons from Class B Crystal Structures.

The glucagon-like peptide 1 (GLP-1) receptor is a class B G protein-coupled receptor (GPCR) that is a key target for treatments for type II diabetes and obesity. This receptor, like other class B GPCRs, displays biased agonism, though the physiologic significance of this is yet to be elucidated. Previous work has implicated R2.60(190), N3.43(240), Q7.49(394), and H6.52(363) as key residues involved in peptide-mediated biased agonism, with R2.60(190), N3.43(240), and Q7.49(394) predicted to form a polar interaction network. In this study, we used novel insight gained from recent crystal structures of the transmembrane domains of the glucagon and corticotropin releasing factor 1 (CRF1) receptors to develop improved models of the GLP-1 receptor that predict additional key molecular interactions with these amino acids. We have introduced E6.53(364)A, N3.43(240)Q, Q7.49(394)N, and N3.43(240)Q/Q7.49(394)N mutations to probe the role of predicted H-bonding and charge-charge interactions in driving cAMP, calcium, or extracellular signal-regulated kinase (ERK) signaling. A polar interaction between E6.53(364) and R2.60(190) was predicted to be important for GLP-1- and exendin-4-, but not oxyntomodulin-mediated cAMP formation and also ERK1/2 phosphorylation. In contrast, Q7.49(394), but not R2.60(190)/E6.53(364) was critical for calcium mobilization for all three peptides. Mutation of N3.43(240) and Q7.49(394) had differential effects on individual peptides, providing evidence for molecular differences in activation transition. Collectively, this work expands our understanding of peptide-mediated signaling from the GLP-1 receptor and the key role that the central polar network plays in these events.

Biased Agonism of Endogenous Opioid Peptides at the µ-Opioid Receptor.

Biased agonism is having a major impact on modern drug discovery, and describes the ability of distinct G protein-coupled receptor (GPCR) ligands to activate different cell signaling pathways, and to result in different physiologic outcomes. To date, most studies of biased agonism have focused on synthetic molecules targeting various GPCRs; however, many of these receptors have multiple endogenous ligands, suggesting that "natural" bias may be an unappreciated feature of these GPCRs. The µ-opioid receptor (MOP) is activated by numerous endogenous opioid peptides, remains an attractive therapeutic target for the treatment of pain, and exhibits biased agonism in response to synthetic opiates. The aim of this study was to rigorously assess the potential for biased agonism in the actions of endogenous opioids at the MOP in a common cellular background, and compare these to the effects of the agonist d-Ala2-N-MePhe4-Gly-ol enkephalin (DAMGO). We investigated activation of G proteins, inhibition of cAMP production, extracellular signal-regulated kinase 1 and 2 phosphorylation, ß-arrestin 1/2 recruitment, and MOP trafficking, and applied a novel analytical method to quantify biased agonism. Although many endogenous opioids displayed signaling profiles similar to that of DAMGO, α-neoendorphin, Met-enkephalin-Arg-Phe, and the putatively endogenous peptide endomorphin-1 displayed particularly distinct bias profiles. These may represent examples of natural bias if it can be shown that they have different signaling properties and physiologic effects in vivo compared with other endogenous opioids. Understanding how endogenous opioids control physiologic processes through biased agonism can reveal vital information required to enable the design of biased opioids with improved pharmacological profiles and treat diseases involving dysfunction of the endogenous opioid system.