Conformation guides molecular efficacy in docking screens of activated β-2 adrenergic G protein coupled receptor

Orphan G protein-coupled receptors: the ongoing search for a home

G protein-coupled receptors (GPCRs) make up the largest receptor superfamily, accounting for 4% of protein-coding genes. Despite the prevalence of such transmembrane receptors, a significant number remain orphans, lacking identified endogenous ligands. Since their conception, the reverse pharmacology approach has been used to characterize such receptors. However, the multifaceted and nuanced nature of GPCR signaling poses a great challenge to their pharmacological elucidation. Considering their therapeutic relevance, the search for native orphan GPCR ligands continues. Despite limited structural input in terms of 3D crystallized structures, with advances in machine-learning approaches, there has been great progress with respect to accurate ligand prediction. Though such an approach proves valuable given that ligand scarcity is the greatest hurdle to orphan GPCR deorphanization, the future pairings of the remaining orphan GPCRs may not necessarily take a one-size-fits-all approach but should be more comprehensive in accounting for numerous nuanced possibilities to cover the full spectrum of GPCR signaling.

Facilitating the drug repurposing with iC/E strategy: A practice on novel nNOS inhibitor discovery

Over the past decades, many existing drugs and clinical/preclinical compounds have been repositioned as new therapeutic indication from which they were originally intended and to treat off-target diseases by targeting their noncognate protein receptors, such as Sildenafil and Paxlovid, termed drug repurposing (DRP). Despite its significant attraction in the current medicinal community, the DRP is usually considered as a matter of accidents that cannot be fulfilled reliably by traditional drug discovery protocol. In this study, we proposed an integrated computational/experimental (iC/E) strategy to facilitate the DRP within a framework of rational drug design, which was practiced on the identification of new neuronal nitric oxide synthase (nNOS) inhibitors from a structurally diverse, functionally distinct drug pool. We demonstrated that the iC/E strategy is very efficient and readily feasible, which confirmed that the phosphodiesterase inhibitor DB06237 showed a high inhibitory potency against nNOS synthase domain, while other two general drugs, i.e. DB02302 and DB08258, can also inhibit the synthase at nanomolar level. Structural bioinformatics analysis revealed diverse noncovalent interactions such as hydrogen bonds, hydrophobic forces and van der Waals contacts across the complex interface of nNOS active site with these identified drugs, conferring both stability and specificity for the complex recognition and association.

Identification of a β-arrestin-biased negative allosteric modulator for the β2-adrenergic receptor

Catecholamine-stimulated β2-adrenergic receptor (β2AR) signaling via the canonical Gs-adenylyl cyclase-cAMP-PKA pathway regulates numerous physiological functions, including the therapeutic effects of exogenous β-agonists in the treatment of airway disease. β2AR signaling is tightly regulated by GRKs and β-arrestins, which together promote β2AR desensitization and internalization as well as downstream signaling, often antithetical to the canonical pathway. Thus, the ability to bias β2AR signaling toward the Gs pathway while avoiding β-arrestin-mediated effects may provide a strategy to improve the functional consequences of β2AR activation. Since attempts to develop Gs-biased agonists and allosteric modulators for the β2AR have been largely unsuccessful, here we screened small molecule libraries for allosteric modulators that selectively inhibit β-arrestin recruitment to the receptor. This screen identified several compounds that met this profile, and, of these, a difluorophenyl quinazoline (DFPQ) derivative was found to be a selective negative allosteric modulator of β-arrestin recruitment to the β2AR while having no effect on β2AR coupling to Gs. DFPQ effectively inhibits agonist-promoted phosphorylation and internalization of the β2AR and protects against the functional desensitization of β-agonist mediated regulation in cell and tissue models. The effects of DFPQ were also specific to the β2AR with minimal effects on the β1AR. Modeling, mutagenesis, and medicinal chemistry studies support DFPQ derivatives binding to an intracellular membrane-facing region of the β2AR, including residues within transmembrane domains 3 and 4 and intracellular loop 2. DFPQ thus represents a class of biased allosteric modulators that targets an allosteric site of the β2AR.

Structure-based discovery of conformationally selective inhibitors of the serotonin transporter

The serotonin transporter (SERT) removes synaptic serotonin and is the target of anti-depressant drugs. SERT adopts three conformations: outward-open, occluded, and inward-open. All known inhibitors target the outward-open state except ibogaine, which has unusual anti-depressant and substance-withdrawal effects, and stabilizes the inward-open conformation. Unfortunately, ibogaine's promiscuity and cardiotoxicity limit the understanding of inward-open state ligands. We docked over 200 million small molecules against the inward-open state of the SERT. Thirty-six top-ranking compounds were synthesized, and thirteen inhibited; further structure-based optimization led to the selection of two potent (low nanomolar) inhibitors. These stabilized an outward-closed state of the SERT with little activity against common off-targets. A cryo-EM structure of one of these bound to the SERT confirmed the predicted geometry. In mouse behavioral assays, both compounds had anxiolytic- and anti-depressant-like activity, with potencies up to 200-fold better than fluoxetine (Prozac), and one substantially reversed morphine withdrawal effects.

Rational design, synthesis, and pharmacological evaluation of a cohort of novel beta-adrenergic receptors ligands enables an assessment of structure-activity relationships

Biomedical applications of molecules that are able to modulate β-adrenergic signaling have become increasingly attractive over the last decade, revealing that β-adrenergic receptors (β-ARs) are key targets for a plethora of therapeutic interventions, including cancer. Despite successes in β-AR drug discovery, identification of β-AR ligands that are useful as selective chemical tools in pharmacological studies of the three β-AR subtypes, or lead compounds for drug development is still a highly challenging task. This is mainly due to the intrinsic plasticity of β-ARs as G protein-coupled receptors in conjunction with the requirement for functional receptor subtype selectivity, tissue specificity and minimal off-target effects. With the aim to provide insight into structure-activity relationships for the three β-AR subtypes, we have synthesized and obtained the pharmacological profile of a series of structurally diverse compounds (named MC) that were designed based on the aryloxy-propanolamine scaffold of SR59230A. Comparative analysis of their predicted binding mode within the active and inactive states of the receptors in combination with their pharmacological profile revealed key structural elements that control their activity as agonists or antagonists, in addition to clues about substituents that mediate selectivity for one receptor subtype over the others. We anticipate that these results will facilitate selective β-AR drug development efforts.

Structure-based discovery of nonopioid analgesics acting through the α2A-adrenergic receptor

Because nonopioid analgesics are much sought after, we computationally docked more than 301 million virtual molecules against a validated pain target, the α2A-adrenergic receptor (α2AAR), seeking new α2AAR agonists chemotypes that lack the sedation conferred by known α2AAR drugs, such as dexmedetomidine. We identified 17 ligands with potencies as low as 12 nanomolar, many with partial agonism and preferential Gi and Go signaling. Experimental structures of α2AAR complexed with two of these agonists confirmed the docking predictions and templated further optimization. Several compounds, including the initial docking hit '9087 [mean effective concentration (EC50) of 52 nanomolar] and two analogs, '7075 and PS75 (EC50 4.1 and 4.8 nanomolar), exerted on-target analgesic activity in multiple in vivo pain models without sedation. These newly discovered agonists are interesting as therapeutic leads that lack the liabilities of opioids and the sedation of dexmedetomidine.

Accelerating GPCR Drug Discovery With Conformation-Stabilizing VHHs

The human genome encodes 850 G protein-coupled receptors (GPCRs), half of which are considered potential drug targets. GPCRs transduce extracellular stimuli into a plethora of vital physiological processes. Consequently, GPCRs are an attractive drug target class. This is underlined by the fact that approximately 40% of marketed drugs modulate GPCRs. Intriguingly 60% of non-olfactory GPCRs have no drugs or candidates in clinical development, highlighting the continued potential of GPCRs as drug targets. The discovery of small molecules targeting these GPCRs by conventional high throughput screening (HTS) campaigns is challenging. Although the definition of success varies per company, the success rate of HTS for GPCRs is low compared to other target families (Fujioka and Omori, 2012; Dragovich et al., 2022). Beyond this, GPCR structure determination can be difficult, which often precludes the application of structure-based drug design approaches to arising HTS hits. GPCR structural studies entail the resource-demanding purification of native receptors, which can be challenging as they are inherently unstable when extracted from the lipid matrix. Moreover, GPCRs are flexible molecules that adopt distinct conformations, some of which need to be stabilized if they are to be structurally resolved. The complexity of targeting distinct therapeutically relevant GPCR conformations during the early discovery stages contributes to the high attrition rates for GPCR drug discovery programs. Multiple strategies have been explored in an attempt to stabilize GPCRs in distinct conformations to better understand their pharmacology. This review will focus on the use of camelid-derived immunoglobulin single variable domains (VHHs) that stabilize disease-relevant pharmacological states (termed ConfoBodies by the authors) of GPCRs, as well as GPCR:signal transducer complexes, to accelerate drug discovery. These VHHs are powerful tools for supporting in vitro screening, deconvolution of complex GPCR pharmacology, and structural biology purposes. In order to demonstrate the potential impact of ConfoBodies on translational research, examples are presented of their role in active state screening campaigns and structure-informed rational design to identify de novo chemical space and, subsequently, how such matter can be elaborated into more potent and selective drug candidates with intended pharmacology.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

Nonantimicrobial Actions of Macrolides: Overview and Perspectives for Future Development

Macrolides are among the most widely prescribed broad spectrum antibacterials, particularly for respiratory infections. It is now recognized that these drugs, in particular azithromycin, also exert time-dependent immunomodulatory actions that contribute to their therapeutic benefit in both infectious and other chronic inflammatory diseases. Their increased chronic use in airway inflammation and, more recently, of azithromycin in COVID-19, however, has led to a rise in bacterial resistance. An additional crucial aspect of chronic airway inflammation, such as chronic obstructive pulmonary disease, as well as other inflammatory disorders, is the loss of epithelial barrier protection against pathogens and pollutants. In recent years, azithromycin has been shown with time to enhance the barrier properties of airway epithelial cells, an action that makes an important contribution to its therapeutic efficacy. In this article, we review the background and evidence for various immunomodulatory and time-dependent actions of macrolides on inflammatory processes and on the epithelium and highlight novel nonantibacterial macrolides that are being studied for immunomodulatory and barrier-strengthening properties to circumvent the risk of bacterial resistance that occurs with macrolide antibacterials. We also briefly review the clinical effects of macrolides in respiratory and other inflammatory diseases associated with epithelial injury and propose that the beneficial epithelial effects of nonantibacterial azithromycin derivatives in chronic inflammation, even given prophylactically, are likely to gain increasing attention in the future. SIGNIFICANCE STATEMENT: Based on its immunomodulatory properties and ability to enhance the protective role of the lung epithelium against pathogens, azithromycin has proven superior to other macrolides in treating chronic respiratory inflammation. A nonantibiotic azithromycin derivative is likely to offer prophylactic benefits against inflammation and epithelial damage of differing causes while preserving the use of macrolides as antibiotics.

BiasNet: A Model to Predict Ligand Bias Toward GPCR Signaling

Signaling bias is a feature of many G protein-coupled receptor (GPCR) targeting drugs with potential clinical implications. Whether it is therapeutically advantageous for a drug to be G protein biased or β-arrestin biased depends on the context of the signaling pathway. Here, we explored GPCR ligands that exhibit biased signaling to gain insights into scaffolds and pharmacophores that lead to bias. More specifically, we considered BiasDB, a database containing information about GPCR biased ligands, and focused our analysis on ligands which show either a G protein or β-arrestin bias. Five different machine learning models were trained on these ligands using 15 different sets of features. Molecular fragments which were important for training the models were analyzed. Two of these fragments (number of secondary amines and number of aromatic amines) were more prevalent in β-arrestin biased ligands. After training a random forest model on HierS scaffolds, we found five scaffolds, which demonstrated G protein or β-arrestin bias. We also conducted t-SNE clustering, observing correspondence between unsupervised and supervised machine learning methods. To increase the applicability of our work, we developed a web implementation of our models, which can predict bias based on user-provided SMILES, drug names, or PubChem CID. Our web implementation is available at: drugdiscovery.utep.edu/biasnet.

An Intracellular Tripeptide Arg-His-Trp of Serum Origin Detected in MCF-7 Cells Is A Possible Agonist to β2 Adrenoceptor

BACKGROUND

The need of agonists and antagonists of β2 adrenoceptor (β2AR) is warranted in various human disease conditions including cancer, cardiovascular and other metabolic disorders. However, the sources of agonists of β2AR are diverse in nature. Interestingly, there is a complete gap in the exploration of agonists of β2AR from serum that is a well-known component of culture media which supports growth and proliferation of normal and cancer cells in vitro.

METHODS

In this paper, we employed a novel vertical tube gel electrophoresis (VTGE)-assisted purification of intracellular metabolites of MCF-7 cells grown in vitro in complete media with fetal bovine serum (FBS). Intracellular metabolites of MCF-7 cells were then analyzed by LC-HRMS. Identified intracellular tripeptides of FBS origin were evaluated for their molecular interactions with various extracellular and intracellular receptors including β2AR (PDB ID: 2RH1) by employing molecular docking and molecular dynamics simulations (MDS). A known agonist of β2AR, isoproterenol was used as a positive control in molecular docking and MDS analyses.

RESULTS

We report here identification of a few novel intracellular tripeptides, namely Arg-His-Trp, (PubChem CID-145453842), Pro-Ile-Glu, (PubChem CID-145457492), Cys-Gln-Gln, (PubChem CID-71471965), Glu-Glu-Lys, (PubChem CID-11441068) and Gly-Cys-Leu (PubChem CID-145455600) of FBS origin in MCF-7 cells. Molecular docking and MDS analyses revealed that among these molecules, the tripeptide Arg-His-Trp shows a favorable binding affinity with β2AR (-9.8 Kcal/mol). The agonistic effect of Arg-His-Trp is significant and comparable with that of a known agonist of β2AR, isoproterenol.

CONCLUSION

In conclusion, we identified a unique Arg-His-Trp tripeptide of FBS origin in MCF-7 cells by employing a novel approach. This unique tripeptide Arg-His-Trp is suggested to be a potential agonist of β2AR and it may have applications in the context of various human diseases like bronchial asthma and chronic obstructive pulmonary disease (COPD).

Ligands of Adrenergic Receptors: A Structural Point of View

Adrenergic receptors are G protein-coupled receptors for epinephrine and norepinephrine. They are targets of many drugs for various conditions, including treatment of hypertension, hypotension, and asthma. Adrenergic receptors are intensively studied in structural biology, displayed for binding poses of different types of ligands. Here, we summarized molecular mechanisms of ligand recognition and receptor activation exhibited by structure. We also reviewed recent advances in structure-based ligand discovery against adrenergic receptors.

Discovery of Novel Allosteric Modulators Targeting an Extra-Helical Binding Site of GLP-1R Using Structure- and Ligand-Based Virtual Screening

Allosteric modulators have emerged with many potential pharmacological advantages as they do not compete the binding of agonist or antagonist to the orthosteric sites but ultimately affect downstream signaling. To identify allosteric modulators targeting an extra-helical binding site of the glucagon-like peptide-1 receptor (GLP-1R) within the membrane environment, the following two computational approaches were applied: structure-based virtual screening with consideration of lipid contacts and ligand-based virtual screening with the maintenance of specific allosteric pocket residue interactions. Verified by radiolabeled ligand binding and cAMP accumulation experiments, two negative allosteric modulators and seven positive allosteric modulators were discovered using structure-based and ligand-based virtual screening methods, respectively. The computational approach presented here could possibly be used to discover allosteric modulators of other G protein-coupled receptors.

Trends in application of advancing computational approaches in GPCR ligand discovery

G protein-coupled receptors (GPCRs) comprise the most important superfamily of protein targets in current ligand discovery and drug development. GPCRs are integral membrane proteins that play key roles in various cellular signaling processes. Therefore, GPCR signaling pathways are closely associated with numerous diseases, including cancer and several neurological, immunological, and hematological disorders. Computer-aided drug design (CADD) can expedite the process of GPCR drug discovery and potentially reduce the actual cost of research and development. Increasing knowledge of biological structures, as well as improvements on computer power and algorithms, have led to unprecedented use of CADD for the discovery of novel GPCR modulators. Similarly, machine learning approaches are now widely applied in various fields of drug target research. This review briefly summarizes the application of rising CADD methodologies, as well as novel machine learning techniques, in GPCR structural studies and bioligand discovery in the past few years. Recent novel computational strategies and feasible workflows are updated, and representative cases addressing challenging issues on olfactory receptors, biased agonism, and drug-induced cardiotoxic effects are highlighted to provide insights into future GPCR drug discovery.

Statistics for the analysis of molecular dynamics simulations: providing P values for agonist-dependent GPCR activation

Molecular dynamics (MD) is the common computational technique for assessing efficacy of GPCR-bound ligands. Agonist efficacy measures the capability of the ligand-bound receptor of reaching the active state in comparison with the free receptor. In this respect, agonists, neutral antagonists and inverse agonists can be considered. A collection of MD simulations of both the ligand-bound and the free receptor are needed to provide reliable conclusions. Variability in the trajectories needs quantification and proper statistical tools for meaningful and non-subjective conclusions. Multiple-factor (time, ligand, lipid) ANOVA with repeated measurements on the time factor is proposed as a suitable statistical method for the analysis of agonist-dependent GPCR activation MD simulations. Inclusion of time factor in the ANOVA model is consistent with the time-dependent nature of MD. Ligand and lipid factors measure agonist and lipid influence on receptor activation. Previously reported MD simulations of adenosine A2a receptor (A2aR) are reanalyzed with this statistical method. TM6–TM3 and TM7–TM3 distances are selected as dependent variables in the ANOVA model. The ligand factor includes the presence or absence of adenosine whereas the lipid factor considers DOPC or DOPG lipids. Statistical analysis of MD simulations shows the efficacy of adenosine and the effect of the membrane lipid composition. Subsequent application of the statistical methodology to NECA A2aR agonist, with resulting P values in consistency with its pharmacological profile, suggests that the method is useful for ligand comparison and potentially for dynamic structure-based virtual screening.

Structure-Based Discovery of Novel Ligands for the Orexin 2 Receptor

The orexin receptors are peptide-sensing G protein-coupled receptors that are intimately linked with regulation of the sleep/wake cycle. We used a recently solved X-ray structure of the orexin receptor subtype 2 in computational docking calculations with the aim to identify additional ligands with unprecedented chemotypes. We found validated ligands with a high hit rate of 29% out of those tested, none of them showing selectivity with respect to the orexin receptor subtype 1. Furthermore, of the higher-affinity compounds examined, none showed any agonist activity. While novel chemical structures can thus be found, selectivity is a challenge owing to the largely identical binding pockets.

A Systematic Review of Inverse Agonism at Adrenoceptor Subtypes

As many, if not most, ligands at G protein-coupled receptor antagonists are inverse agonists, we systematically reviewed inverse agonism at the nine adrenoceptor subtypes. Except for β3-adrenoceptors, inverse agonism has been reported for each of the adrenoceptor subtypes, most often for β2-adrenoceptors, including endogenously expressed receptors in human tissues. As with other receptors, the detection and degree of inverse agonism depend on the cells and tissues under investigation, i.e., they are greatest when the model has a high intrinsic tone/constitutive activity for the response being studied. Accordingly, they may differ between parts of a tissue, for instance, atria vs. ventricles of the heart, and within a cell type, between cellular responses. The basal tone of endogenously expressed receptors is often low, leading to less consistent detection and a lesser extent of observed inverse agonism. Extent inverse agonism depends on specific molecular properties of a compound, but inverse agonism appears to be more common in certain chemical classes. While inverse agonism is a fascinating facet in attempts to mechanistically understand observed drug effects, we are skeptical whether an a priori definition of the extent of inverse agonism in the target product profile of a developmental candidate is a meaningful option in drug discovery and development.

A Focus on Unusual ECL2 Interactions Yields β2 -Adrenergic Receptor Antagonists with Unprecedented Scaffolds

The binding pockets of aminergic G protein-coupled receptors are often targeted by drugs and virtual screening campaigns. In order to find ligands with unprecedented scaffolds for one of the best-investigated receptors of this subfamily, the β2 -adrenergic receptor, we conducted a docking-based screen insisting that molecules would address previously untargeted residues in extracellular loop 2. We here report the discovery of ligands with a previously undescribed coumaran-based scaffold. Furthermore, we provide an analysis of the added value that X-ray structures in different conformations deliver for such docking screens.

Exploring the molecular structures that confer ligand selectivity for galanin type II and III receptors

Galanin receptors (GALRs) belong to the superfamily of G-protein coupled receptors. The three GALR subtypes (GALR1, GALR2, and GALR3) are activated by their endogenous ligands: spexin (SPX) and galanin (GAL). The synthetic SPX-based GALR2-specific agonist, SG2A, plays a dual role in the regulation of appetite and depression-like behaviors. Little is known, however, about the molecular interaction between GALR2 and SG2A. Using site-directed mutagenesis and domain swapping between GALR2 and GALR3, we identified residues in GALR2 that promote interaction with SG2A and residues in GALR3 that inhibit interaction with SG2A. In particular, Phe¹⁰³, Phe¹⁰⁶, and His¹¹⁰ in the transmembrane helix 3 (TM3) domain; Val¹⁹³, Phe¹⁹⁴, and Ser¹⁹⁵ in the TM5 domain; and Leu²⁷³ in the extracellular loop 3 (ECL3) domain of GALR2 provide favorable interactions with the Asn⁵, Ala⁷, Phe¹¹, and Pro¹³ residues of SG2A. Our results explain how SG2A achieves selective interaction with GALR2 and inhibits interaction with GALR3. The results described here can be used broadly for in silico virtual screening of small molecules for the development of GALR subtype-specific agonists and/or antagonists.

Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity

Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even yielded ligand enrichment comparable to or better than that of the D2R and 5-HT2AR crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models.

Comparative Docking to Distinct G Protein-Coupled Receptor Conformations Exclusively Yields Ligands with Agonist Efficacy

G protein-coupled receptors exist in a whole spectrum of conformations that are stabilized by the binding of ligands with different efficacy or intracellular effector proteins. Here, we investigate whether three-dimensional structures of receptor conformations in different states of activation can be used to enrich ligands with agonist behavior in prospective docking calculations. We focused on the β ₂-adrenergic receptor, as it is currently the receptor with the highest number of active-state crystal structures. Comparative docking calculations to distinct conformations of the receptor were used for the in silico prediction of ligands with agonist efficacy. The pharmacology of molecules selected based on these predictions was characterized experimentally, resulting in a hit rate of 37% ligands, all of which were agonists. The ligands furthermore contain a pyrazole moiety that has previously not been described for β ₂-adrenergic receptor ligands, and one of them shows an intrinsic efficacy comparable to salbutamol. SIGNIFICANCE STATEMENT: Structure-based ligand design for G protein-coupled receptors crucially depends on receptor conformation and, hence, their activation state. We explored the influence of using multiple active-conformation X-ray structures on the hit rate of docking calculations to find novel agonists, and how to predict the most fruitful strategy to apply. The results suggest that aggregating the ranks of molecules across docking calculations to more than one active-state structure exclusively yields agonists.

Discovery of β-arrestin-biased β2-adrenoceptor agonists from 2-amino-2-phenylethanol derivatives

β-Arrestins are a small family of proteins important for signal transduction at G protein-coupled receptors (GPCRs). β-Arrestins are involved in the desensitization of GPCRs. Recently, biased ligands possessing different efficacies in activating the G protein- versus the β-arrestin-dependent signals downstream of a single GPCR have emerged, which can be used to selectively modulate GPCR signal transduction in such a way that desirable signals are enhanced to produce therapeutic effects while undesirable signals of the same GPCR are suppressed to avoid side effects. In the present study, we evaluated agonist bias for compounds developed along a drug discovery project of β₂-adrenoceptor agonists. About 150 compounds, including derivatives of fenoterol, 2-amino-1-phenylethanol and 2-amino-2-phenylethanol, were obtained or synthesized, and initially screened for their β-adrenoceptor-mediated activities in the guinea pig tracheal smooth muscle relaxation assay or the cardiomyocyte contractility assay. Nineteen bioactive compounds were further assessed using both the HTRF cAMP assay and the PathHunter β-arrestin assay. Their concentration-response data in stimulating cAMP synthesis and β-arrestin recruitment were applied to the Black-Leff operational model for ligand bias quantitation. As a result, three compounds (L-2, L-4, and L-12) with the core structure of 5-(1-amino-2-hydroxyethyl)-8-hydroxyquinolin-2(1H)-one were identified as a new series of β-arrestin-biased β₂-adrenoceptor agonists, whereas salmeterol was found to be G_s-biased. These findings would facilitate the development of novel drugs for the treatment of both heart failure and asthma.

D2 Dopamine Receptor G Protein-Biased Partial Agonists Based on Cariprazine

Functionally selective G protein-coupled receptor ligands are valuable tools for deciphering the roles of downstream signaling pathways that potentially contribute to therapeutic effects versus side effects. Recently, we discovered both Gi/o-biased and β-arrestin2-biased D2 receptor agonists based on the Food and Drug Administration (FDA)-approved drug aripiprazole. In this work, based on another FDA-approved drug, cariprazine, we conducted a structure-functional selectivity relationship study and discovered compound 38 (MS1768) as a potent partial agonist that selectively activates the Gi/o pathway over β-arrestin2. Unlike the dual D2R/D3R partial agonist cariprazine, compound 38 showed selective agonist activity for D2R over D3R. In fact, compound 38 exhibited potent antagonism of dopamine-stimulated β-arrestin2 recruitment. In our docking studies, compound 38 directly interacts with S1935.42 on TM5 but has no interactions with extracellular loop 2, which appears to be in contrast to the binding poses of D2R β-arrestin2-biased ligands. In in vivo studies, compound 38 showed high D2R receptor occupancy in mice and effectively inhibited phencyclidine-induced hyperlocomotion.

Recent advances in computational studies of GPCR-G protein interactions

Protein-protein interactions are key in cellular signaling. G protein-coupled receptors (GPCRs), the largest superfamily of human membrane proteins, are able to transduce extracellular signals (e.g., hormones and neurotransmitters) to intracellular proteins, in particular the G proteins. Since GPCRs serve as primary targets of ~1/3 of currently marketed drugs, it is important to understand mechanisms of GPCR signaling in order to design selective and potent drug molecules. This chapter focuses on recent advances in computational studies of the GPCR-G protein interactions using bioinformatics, protein-protein docking and molecular dynamics simulation approaches.

Approaches for Differentiation and Interconverting GPCR Agonists and Antagonists

Predicting the functional preferences of the ligands was always a highly demanding task, much harder that predicting whether a ligand can bind to the receptor. This is because of significant similarities of agonists, antagonists and inverse agonists which are binding usually in the same binding site of the receptor and only small structural changes can push receptor toward a particular activation state. For G protein-coupled receptors, due to a large progress in crystallization techniques and also in receptor thermal stabilization, it was possible to obtain a large number of high-quality structures of complexes of these receptors with agonists and non-agonists. Additionally, the long-time-scale molecular dynamics simulations revealed how the activation processes of GPCRs can take place. Using both theoretical and experimental knowledge it was possible to employ many clever and sophisticated methods which can help to differentiate agonists and non-agonists, so one can interconvert them in search of the optimal drug.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the "golden age for GPCR structural biology." Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand- and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

Structure-based discovery of selective positive allosteric modulators of antagonists for the M2 muscarinic acetylcholine receptor

The orthosteric binding sites of the five muscarinic acetylcholine receptor (mAChR) subtypes are highly conserved, making the development of selective antagonists challenging. The allosteric sites of these receptors are more variable, allowing one to imagine allosteric modulators that confer subtype selectivity, which would reduce the major off-target effects of muscarinic antagonists. Accordingly, a large library docking campaign was prosecuted seeking unique positive allosteric modulators (PAMs) for antagonists, ultimately revealing a PAM that substantially potentiates antagonist binding leading to subtype selectivity at the M₂ mAChR. This study supports the feasibility of discovering PAMs that can convert an armamentarium of potent but nonselective G-protein–coupled receptor (GPCR) antagonist drugs into subtype-selective reagents.

Subtype-selective antagonists for muscarinic acetylcholine receptors (mAChRs) have long been elusive, owing to the highly conserved orthosteric binding site. However, allosteric sites of these receptors are less conserved, motivating the search for allosteric ligands that modulate agonists or antagonists to confer subtype selectivity. Accordingly, a 4.6 million-molecule library was docked against the structure of the prototypical M₂ mAChR, seeking molecules that specifically stabilized antagonist binding. This led us to identify a positive allosteric modulator (PAM) that potentiated the antagonist N-methyl scopolamine (NMS). Structure-based optimization led to compound ’628, which enhanced binding of NMS, and the drug scopolamine itself, with a cooperativity factor (α) of 5.5 and a K_B of 1.1 μM, while sparing the endogenous agonist acetylcholine. NMR spectral changes determined for methionine residues reflected changes in the allosteric network. Moreover, ’628 slowed the dissociation rate of NMS from the M₂ mAChR by 50-fold, an effect not observed at the other four mAChR subtypes. The specific PAM effect of ’628 on NMS antagonism was conserved in functional assays, including agonist stimulation of [³⁵S]GTPγS binding and ERK 1/2 phosphorylation. Importantly, the selective allostery between ’628 and NMS was retained in membranes from adult rat hypothalamus and in neonatal rat cardiomyocytes, supporting the physiological relevance of this PAM/antagonist approach. This study supports the feasibility of discovering PAMs that confer subtype selectivity to antagonists; molecules like ’628 can convert an armamentarium of potent but nonselective GPCR antagonist drugs into subtype-selective reagents, thus reducing their off-target effects.

Identifying Functional Hotspot Residues for Biased Ligand Design in G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) mediate multiple signaling pathways in the cell, depending on the agonist that activates the receptor and multiple cellular factors. Agonists that show higher potency to specific signaling pathways over others are known as "biased agonists" and have been shown to have better therapeutic index. Although biased agonists are desirable, their design poses several challenges to date. The number of assays to identify biased agonists seems expensive and tedious. Therefore, computational methods that can reliably calculate the possible bias of various ligands ahead of experiments and provide guidance, will be both cost and time effective. In this work, using the mechanism of allosteric communication from the extracellular region to the intracellular transducer protein coupling region in GPCRs, we have developed a computational method to calculate ligand bias ahead of experiments. We have validated the method for several β-arrestin-biased agonists in β₂-adrenergic receptor (β2AR), serotonin receptors 5-HT1B and 5-HT2B and for G-protein-biased agonists in the κ-opioid receptor. Using this computational method, we also performed a blind prediction followed by experimental testing and showed that the agonist carmoterol is β-arrestin-biased in β2AR. Additionally, we have identified amino acid residues in the biased agonist binding site in both β2AR and κ-opioid receptors that are involved in potentiating the ligand bias. We call these residues functional hotspots, and they can be used to derive pharmacophores to design biased agonists in GPCRs.

GPCRs: What Can We Learn from Molecular Dynamics Simulations?

Advances in the structural biology of G-protein Coupled Receptors have resulted in a significant step forward in our understanding of how this important class of drug targets function at the molecular level. However, it has also become apparent that they are very dynamic molecules, and moreover, that the underlying dynamics is crucial in shaping the response to different ligands. Molecular dynamics simulations can provide unique insight into the dynamic properties of GPCRs in a way that is complementary to many experimental approaches. In this chapter, we describe progress in three distinct areas that are particularly difficult to study with other techniques: atomic level investigation of the conformational changes that occur when moving between the various states that GPCRs can exist in, the pathways that ligands adopt during binding/unbinding events and finally, the influence of lipids on the conformational dynamics of GPCRs.

Structure-inspired design of β-arrestin-biased ligands for aminergic GPCRs

Development of biased ligands targeting G protein-coupled receptors (GPCRs) is a promising approach for current drug discovery. Although structure-based drug design of biased agonists remains challenging even with an abundance of GPCR crystal structures, we present an approach for translating GPCR structural data into β-arrestin-biased ligands for aminergic GPCRs. We identified specific amino acid-ligand contacts at transmembrane helix 5 (TM5) and extracellular loop 2 (EL2) responsible for Gi/o and β-arrestin signaling, respectively, and targeted those residues to develop biased ligands. For these ligands, we found that bias is conserved at other aminergic GPCRs that retain similar residues at TM5 and EL2. Our approach provides a template for generating arrestin-biased ligands by modifying predicted ligand interactions that block TM5 interactions and promote EL2 interactions. This strategy could facilitate the structure-guided design of arrestin-biased ligands at other GPCRs, including polypharmacological biased ligands.

Methods for Virtual Screening of GPCR Targets: Approaches and Challenges

Virtual screening (VS) has become an integral part of the drug discovery process and is a valuable tool for finding novel chemical starting points for GPCR targets. Ligand-based VS makes use of biochemical data for known, active compounds and has been applied successfully to many diverse GPCRs. Recent progress in GPCR X-ray crystallography has made it possible to incorporate detailed structural information into the VS process. This chapter outlines the latest VS techniques along with examples that highlight successful applications of these methods. Best practices for increasing the likelihood of VS success, as well as ongoing challenges, are also discussed.

Structure-Guided Screening for Functionally Selective D2 Dopamine Receptor Ligands from a Virtual Chemical Library

Functionally selective ligands stabilize conformations of G protein-coupled receptors (GPCRs) that induce a preference for signaling via a subset of the intracellular pathways activated by the endogenous agonists. The possibility to fine-tune the functional activity of a receptor provides opportunities to develop drugs that selectively signal via pathways associated with a therapeutic effect and avoid those causing side effects. Animal studies have indicated that ligands displaying functional selectivity at the D₂ dopamine receptor (D₂R) could be safer and more efficacious drugs against neuropsychiatric diseases. In this work, computational design of functionally selective D₂R ligands was explored using structure-based virtual screening. Molecular docking of known functionally selective ligands to a D₂R homology model indicated that such compounds were anchored by interactions with the orthosteric site and extended into a common secondary pocket. A tailored virtual library with close to 13 000 compounds bearing 2,3-dichlorophenylpiperazine, a privileged orthosteric scaffold, connected to diverse chemical moieties via a linker was docked to the D₂R model. Eighteen top-ranked compounds that occupied both the orthosteric and allosteric site were synthesized, leading to the discovery of 16 partial agonists. A majority of the ligands had comparable maximum effects in the G protein and β-arrestin recruitment assays, but a subset displayed preference for a single pathway. In particular, compound 4 stimulated β-arrestin recruitment (EC₅₀ = 320 nM, E_max = 16%) but had no detectable G protein signaling. The use of structure-based screening and virtual libraries to discover GPCR ligands with tailored functional properties will be discussed.

Recent Advances in Structure-Based Drug Design Targeting Class A G Protein-Coupled Receptors Utilizing Crystal Structures and Computational Simulations

G protein-coupled receptors (GPCRs) represent the largest and most physiologically important integral membrane protein family, and these receptors respond to a wide variety of physiological and environmental stimuli. GPCRs are among the most critical therapeutic targets for numerous human diseases, and approximately one-third of the currently marketed drugs target this receptor family. The recent breakthroughs in GPCR structural biology have significantly contributed to our understanding of GPCR function, ligand binding, and pharmacological action as well as to the design of new drugs. This perspective highlights the latest advances in GPCR structures with a focus on the receptor-ligand interactions of each receptor family in class A nonrhodopsin GPCRs as well as the structural features for their activation, biased signaling, and allosteric mechanisms. The current state-of-the-art methodologies of structure-based drug design (SBDD) approaches in the GPCR research field are also discussed.

Investigating allosteric effects on the functional dynamics of β2-adrenergic ternary complexes with enhanced-sampling simulations

Signalling by G-protein coupled receptors usually occurs via ternary complexes formed under cooperative binding between the receptor, a ligand and an intracellular binding partner (a G-protein or β-arrestin). While a global rational for allosteric effects in ternary complexes would be of great help in designing ligands with specific effects, the paucity of structural data for ternary complexes with β-arrestin, together with the intrinsic difficulty of characterizing the dynamics involved in the allosteric coupling, have hindered the efforts to devise such a model. Here we have used enhanced-sampling atomistic molecular-dynamics simulations to investigate the dynamics and complex formation mechanisms of both β-arrestin- and Gs-complexes with the β2-adrenergic receptor (ADRB2) in its apo-form and in the presence of four small ligands that exert different allosteric effects. Our results suggest that the structure and dynamics of arrestin-ADRB2 complexes depend strongly on the nature of the small ligands. The complexes exhibit a variety of different coupling orientations in terms of the depth of the finger loop in the receptor and activation states of ADRB2. The simulations also allow us to characterize the cooperativity between the ligand and intracellular binding partner (IBP). Based on the complete and consistent results, we propose an experimentally testable extended ternary complex model, where direction of the cooperative effect between ligand and IBP (positive or negative) and its magnitude are predicted to be a characteristic of the ligand signaling bias. This paves the avenue to the rational design of ligands with specific functional effects.

Structure-Based Discovery of New Antagonist and Biased Agonist Chemotypes for the Kappa Opioid Receptor

The ongoing epidemics of opioid overdose raises an urgent need for effective antiaddiction therapies and addiction-free painkillers. The κ-opioid receptor (KOR) has emerged as a promising target for both indications, raising demand for new chemotypes of KOR antagonists as well as G-protein-biased agonists. We employed the crystal structure of the KOR-JDTic complex and ligand-optimized structural templates to perform virtual screening of available compound libraries for new KOR ligands. The prospective virtual screening campaign yielded a high 32% hit rate, identifying novel fragment-like and lead-like chemotypes of KOR ligands. A round of optimization resulted in 11 new submicromolar KOR binders (best K_i = 90 nM). Functional assessment confirmed at least two compounds as potent KOR antagonists, while compound 81 was identified as a potent G_i biased agonist for KOR with minimal β-arrestin recruitment. These results support virtual screening as an effective tool for discovery of new lead chemotypes with therapeutically relevant functional profiles.

Ligand Discovery for a Peptide-Binding GPCR by Structure-Based Screening of Fragment- and Lead-Like Chemical Libraries

Peptide-recognizing G protein-coupled receptors (GPCRs) are promising therapeutic targets but often resist drug discovery efforts. Determination of crystal structures for peptide-binding GPCRs has provided opportunities to explore structure-based methods in lead development. Molecular docking screens of two chemical libraries, containing either fragment- or lead-like compounds, against a neurotensin receptor 1 crystal structure allowed for a comparison between different drug development strategies for peptide-binding GPCRs. A total of 2.3 million molecules were screened computationally, and 25 fragments and 27 leads that were top-ranked in each library were selected for experimental evaluation. Of these, eight fragments and five leads were confirmed as ligands by surface plasmon resonance. The hit rate for the fragment screen (32%) was thus higher than for the lead-like library (19%), but the affinities of the fragments were ∼100-fold lower. Both screens returned unique scaffolds and demonstrated that a crystal structure of a stabilized peptide-binding GPCR can guide the discovery of small-molecule agonists. The complementary advantages of exploring fragment- and lead-like chemical space suggest that these strategies should be applied synergistically in structure-based screens against challenging GPCR targets.

Recent Advances and Applications of Molecular Docking to G Protein-Coupled Receptors

The growing number of studies on G protein-coupled receptors (GPCRs) family are a source of noticeable improvement in our understanding of the functioning of these proteins. GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in the spotlight of medicinal chemistry. A deeper insight into the underlying mechanisms of interesting phenomena observed in GPCRs, such as biased signaling or allosteric modulation, can be gained with experimental and computational studies. The latter play an important role in this process, since they allow for observations on scales inaccessible for most other methods. One of the key steps in such studies is proper computational reconstruction of actual ligand-receptor or protein-protein interactions, a process called molecular docking. A number of improvements and innovative applications of this method were documented recently. In this review, we focus particularly on innovations in docking to GPCRs.

Identifying ligands at orphan GPCRs: current status using structure-based approaches

GPCRs are the most successful pharmaceutical targets in history. Nevertheless, the pharmacology of many GPCRs remains inaccessible as their endogenous or exogenous modulators have not been discovered. Tools that explore the physiological functions and pharmacological potential of these 'orphan' GPCRs, whether they are endogenous and/or surrogate ligands, are therefore of paramount importance. Rates of receptor deorphanization determined by traditional reverse pharmacology methods have slowed, indicating a need for the development of more sophisticated and efficient ligand screening approaches. Here, we discuss the use of structure-based ligand discovery approaches to identify small molecule modulators for exploring the function of orphan GPCRs. These studies have been buoyed by the growing number of GPCR crystal structures solved in the past decade, providing a broad range of template structures for homology modelling of orphans. This review discusses the methods used to establish the appropriate signalling assays to test orphan receptor activity and provides current examples of structure-based methods used to identify ligands of orphan GPCRs. Linked Articles This article is part of a themed section on Molecular Pharmacology of G Protein-Coupled Receptors. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v173.20/issuetoc.

Structure-based discovery of opioid analgesics with reduced side effects

Morphine is an alkaloid from the opium poppy used to treat pain. The potentially lethal side effects of morphine and related opioids-which include fatal respiratory depression-are thought to be mediated by μ-opioid-receptor (μOR) signalling through the β-arrestin pathway or by actions at other receptors. Conversely, G-protein μOR signalling is thought to confer analgesia. Here we computationally dock over 3 million molecules against the μOR structure and identify new scaffolds unrelated to known opioids. Structure-based optimization yields PZM21-a potent Gi activator with exceptional selectivity for μOR and minimal β-arrestin-2 recruitment. Unlike morphine, PZM21 is more efficacious for the affective component of analgesia versus the reflexive component and is devoid of both respiratory depression and morphine-like reinforcing activity in mice at equi-analgesic doses. PZM21 thus serves as both a probe to disentangle μOR signalling and a therapeutic lead that is devoid of many of the side effects of current opioids.

Accelerated structure-based design of chemically diverse allosteric modulators of a muscarinic G protein-coupled receptor

Design of ligands that provide receptor selectivity has emerged as a new paradigm for drug discovery of G protein-coupled receptors, and may, for certain families of receptors, only be achieved via identification of chemically diverse allosteric modulators. Here, the extracellular vestibule of the M2 muscarinic acetylcholine receptor (mAChR) is targeted for structure-based design of allosteric modulators. Accelerated molecular dynamics (aMD) simulations were performed to construct structural ensembles that account for the receptor flexibility. Compounds obtained from the National Cancer Institute (NCI) were docked to the receptor ensembles. Retrospective docking of known ligands showed that combining aMD simulations with Glide induced fit docking (IFD) provided much-improved enrichment factors, compared with the Glide virtual screening workflow. Glide IFD was thus applied in receptor ensemble docking, and 38 top-ranked NCI compounds were selected for experimental testing. In [(3)H]N-methylscopolamine radioligand dissociation assays, approximately half of the 38 lead compounds altered the radioligand dissociation rate, a hallmark of allosteric behavior. In further competition binding experiments, we identified 12 compounds with affinity of ≤30 μM. With final functional experiments on six selected compounds, we confirmed four of them as new negative allosteric modulators (NAMs) and one as positive allosteric modulator of agonist-mediated response at the M2 mAChR. Two of the NAMs showed subtype selectivity without significant effect at the M1 and M3 mAChRs. This study demonstrates an unprecedented successful structure-based approach to identify chemically diverse and selective GPCR allosteric modulators with outstanding potential for further structure-activity relationship studies.

Conformationally selective RNA aptamers allosterically modulate the β2-adrenoceptor

G-protein-coupled receptor (GPCR) ligands function by stabilizing multiple, functionally distinct receptor conformations. This property underlies the ability of 'biased agonists' to activate specific subsets of a given receptor's signaling profile. However, stabilizing distinct active GPCR conformations to enable structural characterization of mechanisms underlying GPCR activation remains difficult. These challenges have accentuated the need for receptor tools that allosterically stabilize and regulate receptor function through unique, previously unappreciated mechanisms. Here, using a highly diverse RNA library combined with advanced selection strategies involving state-of-the-art next-generation sequencing and bioinformatics analyses, we identify RNA aptamers that bind a prototypical GPCR, the β2-adrenoceptor (β2AR). Using biochemical, pharmacological, and biophysical approaches, we demonstrate that these aptamers bind with nanomolar affinity at defined surfaces of the receptor, allosterically stabilizing active, inactive, and ligand-specific receptor conformations. The discovery of RNA aptamers as allosteric GPCR modulators significantly expands the diversity of ligands available to study the structural and functional regulation of GPCRs.

DREADDs for Neuroscientists

To understand brain function, it is essential that we discover how cellular signaling specifies normal and pathological brain function. In this regard, chemogenetic technologies represent valuable platforms for manipulating neuronal and non-neuronal signal transduction in a cell-type-specific fashion in freely moving animals. Designer Receptors Exclusively Activated by Designer Drugs (DREADD)-based chemogenetic tools are now commonly used by neuroscientists to identify the circuitry and cellular signals that specify behavior, perceptions, emotions, innate drives, and motor functions in species ranging from flies to nonhuman primates. Here I provide a primer on DREADDs highlighting key technical and conceptual considerations and identify challenges for chemogenetics going forward.

Function-specific virtual screening for GPCR ligands using a combined scoring method

The ability of scoring functions to correctly select and rank docking poses of small molecules in protein binding sites is highly target dependent, which presents a challenge for structure-based drug discovery. Here we describe a virtual screening method that combines an energy-based docking scoring function with a molecular interaction fingerprint (IFP) to identify new ligands based on G protein-coupled receptor (GPCR) crystal structures. The consensus scoring method is prospectively evaluated by: 1) the discovery of chemically novel, fragment-like, high affinity histamine H₁ receptor (H₁R) antagonists/inverse agonists, 2) the selective structure-based identification of ß₂-adrenoceptor (ß₂R) agonists, and 3) the experimental validation and comparison of the combined and individual scoring approaches. Systematic retrospective virtual screening simulations allowed the definition of scoring cut-offs for the identification of H₁R and ß₂R ligands and the selection of an optimal ß-adrenoceptor crystal structure for the discrimination between ß₂R agonists and antagonists. The consensus approach resulted in the experimental validation of 53% of the ß₂R and 73% of the H₁R virtual screening hits with up to nanomolar affinities and potencies. The selective identification of ß₂R agonists shows the possibilities of structure-based prediction of GPCR ligand function by integrating protein-ligand binding mode information.

Structure-Based Discovery of Novel and Selective 5-Hydroxytryptamine 2B Receptor Antagonists for the Treatment of Irritable Bowel Syndrome

Here we employed structure-based ligand discovery techniques to explore a recently determined crystal structure of the 5-hydroxytryptamine 2B (5-HT2B) receptor. Ten compounds containing a novel chemical scaffold were identified; among them, seven molecules were active in cellular function assays with the most potent one exhibiting an IC50 value of 27.3 nM. We then systematically probed the binding characteristics of this scaffold by designing, synthesizing, and testing a series of structural modifications. The structure-activity relationship studies strongly support our predicted binding model. The binding profiling across a panel of 11 5-HT receptors indicated that these compounds are highly selective for the 5-HT2B receptor. Oral administration of compound 15 (30 mg/kg) produced significant attenuation of visceral hypersensitivity in a rat model of irritable bowel syndrome (IBS). We expect this novel scaffold will serve as the foundation for the development of 5-HT2B antagonists for the treatment of IBS.