Xylazine is an agonist at kappa opioid receptors and exhibits sex-specific responses to opioid antagonism.

Xylazine is in the unregulated drug supply at increasing rates, usually combined with fentanyl, necessitating understanding of its pharmacology. Despite commentary from politicians, and public health officials, it is unknown how xylazine impacts naloxone efficacy, and. few studies have examined it alone. Here, we examine the impact of xylazine alone and in combination with fentanyl on several behaviors in mice. Surprisingly, naloxone precipitates withdrawal from xylazine and fentanyl/xylazine coadministration, with enhanced sensitivity in females. Further, xylazine is a full agonist at kappa opioid receptors, a potential mechanism for its naloxone sensitivity. Finally, we demonstrate surprising effects of xylazine to kappa opioid antagonism, which are relevant for public health considerations. These data address an ongoing health crisis and will help inform critical policy and healthcare decisions.

A neurodevelopmental disorder mutation locks G proteins in the transitory pre-activated state.

Many neurotransmitter receptors activate G proteins through exchange of GDP for GTP. The intermediate nucleotide-free state has eluded characterization, due largely to its inherent instability. Here we characterize a G protein variant associated with a rare neurological disorder in humans. GαoK46E has a charge reversal that clashes with the phosphate groups of GDP and GTP. As anticipated, the purified protein binds poorly to guanine nucleotides yet retains wild-type affinity for G protein ßγ subunits. In cells with physiological concentrations of nucleotide, GαoK46E forms a stable complex with receptors and Gßγ, impeding effector activation. Further, we demonstrate that the mutant can be easily purified in complex with dopamine-bound D2 receptors, and use cryo-electron microscopy to determine the structure, including both domains of Gαo, without nucleotide or stabilizing nanobodies. These findings reveal the molecular basis for the first committed step of G protein activation, establish a mechanistic basis for a neurological disorder, provide a simplified strategy to determine receptor-G protein structures, and a method to detect high affinity agonist binding in cells.

An shRNA screen in primary human beta cells identifies the serotonin 1F receptor as a negative regulator of survival during transplant.

Islet transplantation can cure type 1 diabetes, but peri-transplant beta cell death limits this procedure to those with low insulin requirements. Improving human beta cell survival or proliferation may make islet transplantation a possibility for more type 1 patients. To identify novel regulators of beta cell survival and proliferation, we conducted a pooled small hairpin RNA (shRNA) screen in primary human beta cells transplanted into immunocompromised mice. shRNAs targeting several cyclin dependent kinase inhibitors were enriched after transplant. Here, we focused on the Gi/o-coupled GPCR, serotonin 1F receptor ( HTR1F, 5-HT 1F ) which our screen identified as a negative regulator of beta cell numbers after transplant. In vitro , 5-HT 1F knockdown induced human beta cell proliferation but only when combined with harmine and exendin-4. In vivo , knockdown of 5-HT 1F reduced beta cell death during transplant. To demonstrate the feasibility of targeting 5-HT 1F in islet transplant, we identified and validated a small molecule 5-HT 1F antagonist. This antagonist increased glucose stimulated insulin secretion from primary human islets and cAMP accumulation in primary human beta cells. Finally, the 5-HT 1F antagonist improved glycemia in marginal mass, human islet transplants into immunocompromised mice. We identify 5-HT 1F as a novel druggable target to improve human beta cell survival in the setting of islet transplantation. One Sentence Summary: Serotonin 1F receptor (5-HT 1F ) negatively regulates insulin secretion and beta cell survival during transplant.

Molecular basis of proton-sensing by G protein-coupled receptors.

Three proton-sensing G protein-coupled receptors (GPCRs), GPR4, GPR65, and GPR68, respond to changes in extracellular pH to regulate diverse physiology and are implicated in a wide range of diseases. A central challenge in determining how protons activate these receptors is identifying the set of residues that bind protons. Here, we determine structures of each receptor to understand the spatial arrangement of putative proton sensing residues in the active state. With a newly developed deep mutational scanning approach, we determined the functional importance of every residue in proton activation for GPR68 by generating ~9,500 mutants and measuring effects on signaling and surface expression. This unbiased screen revealed that, unlike other proton-sensitive cell surface channels and receptors, no single site is critical for proton recognition in GPR68. Instead, a network of titratable residues extend from the extracellular surface to the transmembrane region and converge on canonical class A GPCR activation motifs to activate proton-sensing GPCRs. More broadly, our approach integrating structure and unbiased functional interrogation defines a new framework for understanding the rich complexity of GPCR signaling.

Docking for EP4R antagonists active against inflammatory pain.

The lipid prostaglandin E2 (PGE2) mediates inflammatory pain by activating G protein-coupled receptors, including the prostaglandin E2 receptor 4 (EP4R). Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce nociception by inhibiting prostaglandin synthesis, however, the disruption of upstream prostanoid biosynthesis can lead to pleiotropic effects including gastrointestinal bleeding and cardiac complications. In contrast, by acting downstream, EP4R antagonists may act specifically as anti-inflammatory agents and, to date, no selective EP4R antagonists have been approved for human use. In this work, seeking to diversify EP4R antagonist scaffolds, we computationally dock over 400 million compounds against an EP4R crystal structure and experimentally validate 71 highly ranked, de novo synthesized molecules. Further, we show how structure-based optimization of initial docking hits identifies a potent and selective antagonist with 16 nanomolar potency. Finally, we demonstrate favorable pharmacokinetics for the discovered compound as well as anti-allodynic and anti-inflammatory activity in several preclinical pain models in mice.

Nonspecific membrane bilayer perturbations by ivermectin underlie SARS-CoV-2 in vitro activity.

Since it was proposed as a potential host-directed antiviral agent for SARS-CoV-2, the antiparasitic drug ivermectin has been investigated thoroughly in clinical trials, which have provided insufficient support for its clinical efficacy. To examine the potential for ivermectin to be repurposed as an antiviral agent, we therefore undertook a series of preclinical studies. Consistent with early reports, ivermectin decreased SARS-CoV-2 viral burden in in vitro models at low micromolar concentrations, five- to ten-fold higher than the reported toxic clinical concentration. At similar concentrations, ivermectin also decreased cell viability and increased biomarkers of cytotoxicity and apoptosis. Further mechanistic and profiling studies revealed that ivermectin nonspecifically perturbs membrane bilayers at the same concentrations where it decreases the SARS-CoV-2 viral burden, resulting in nonspecific modulation of membrane-based targets such as G-protein coupled receptors and ion channels. These results suggest that a primary molecular mechanism for the in vitro antiviral activity of ivermectin may be nonspecific membrane perturbation, indicating that ivermectin is unlikely to be translatable into a safe and effective antiviral agent. These results and experimental workflow provide a useful paradigm for performing preclinical studies on (pandemic-related) drug repurposing candidates.

De Novo Design of κ-Opioid Receptor Antagonists Using a Generative Deep-Learning Framework.

Likely effective pharmacological interventions for the treatment of opioid addiction include attempts to attenuate brain reward deficits during periods of abstinence. Pharmacological blockade of the κ-opioid receptor (KOR) has been shown to abolish brain reward deficits in rodents during withdrawal, as well as to reduce the escalation of opioid use in rats with extended access to opioids. Although KOR antagonists represent promising candidates for the treatment of opioid addiction, very few potent selective KOR antagonists are known to date and most of them exhibit significant safety concerns. Here, we used a generative deep-learning framework for the de novo design of chemotypes with putative KOR antagonistic activity. Molecules generated by models trained with this framework were prioritized for chemical synthesis based on their predicted optimal interactions with the receptor. Our models and proposed training protocol were experimentally validated by binding and functional assays.

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.

De Novo Design of κ-Opioid Receptor Antagonists Using a Generative Deep Learning Framework.

Likely effective pharmacological interventions for the treatment of opioid addiction include attempts to attenuate brain reward deficits during periods of abstinence. Pharmacological blockade of the κ-opioid receptor (KOR) has been shown to abolish brain reward deficits in rodents during withdrawal, as well as to reduce the escalation of opioid use in rats with extended access to opioids. Although KOR antagonists represent promising candidates for the treatment of opioid addiction, very few potent selective KOR antagonists are known to date and most of them exhibit significant safety concerns. Here, we used a generative deep learning framework for the de novo design of chemotypes with putative KOR antagonistic activity. Molecules generated by models trained with this framework were prioritized for chemical synthesis based on their predicted optimal interactions with the receptor. Our models and proposed training protocol were experimentally validated by binding and functional assays.

Structural genomics of the human dopamine receptor system.

The dopaminergic system, including five dopamine receptors (D1R to D5R), plays essential roles in the central nervous system (CNS); and ligands that activate dopamine receptors have been used to treat many neuropsychiatric disorders, including Parkinson's Disease (PD) and schizophrenia. Here, we report cryo-EM structures of all five subtypes of human dopamine receptors in complex with G protein and bound to the pan-agonist, rotigotine, which is used to treat PD and restless legs syndrome. The structures reveal the basis of rotigotine recognition in different dopamine receptors. Structural analysis together with functional assays illuminate determinants of ligand polypharmacology and selectivity. The structures also uncover the mechanisms of dopamine receptor activation, unique structural features among the five receptor subtypes, and the basis of G protein coupling specificity. Our work provides a comprehensive set of structural templates for the rational design of specific ligands to treat CNS diseases targeting the dopaminergic system.

Structural insights into angiotensin receptor signaling modulation by balanced and biased agonists.

The peptide hormone angiotensin II regulates blood pressure mainly through the type 1 angiotensin II receptor AT1 R and its downstream signaling proteins Gq and ß-arrestin. AT1 R blockers, clinically used as antihypertensive drugs, inhibit both signaling pathways, whereas AT1 R ß-arrestin-biased agonists have shown great potential for the treatment of acute heart failure. Here, we present a cryo-electron microscopy (cryo-EM) structure of the human AT1 R in complex with a balanced agonist, Sar1 -AngII, and Gq protein at 2.9 Å resolution. This structure, together with extensive functional assays and computational modeling, reveals the molecular mechanisms for AT1 R signaling modulation and suggests that a major hydrogen bond network (MHN) inside the receptor serves as a key regulator of AT1 R signal transduction from the ligand-binding pocket to both Gq and ß-arrestin pathways. Specifically, we found that the MHN mutations N1113.35 A and N2947.45 A induce biased signaling to Gq and ß-arrestin, respectively. These insights should facilitate AT1 R structure-based drug discovery for the treatment of cardiovascular diseases.

Neurotensin Receptor Allosterism Revealed in Complex with a Biased Allosteric Modulator.

The NTSR1 neurotensin receptor (NTSR1) is a G protein-coupled receptor (GPCR) found in the brain and peripheral tissues with neurotensin (NTS) being its endogenous peptide ligand. In the brain, NTS modulates dopamine neuronal activity, induces opioid-independent analgesia, and regulates food intake. Recent studies indicate that biasing NTSR1 toward ß-arrestin signaling can attenuate the actions of psychostimulants and other drugs of abuse. Here, we provide the cryoEM structures of NTSR1 ternary complexes with heterotrimeric Gq and GoA with and without the brain-penetrant small-molecule SBI-553. In functional studies, we discovered that SBI-553 displays complex allosteric actions exemplified by negative allosteric modulation for G proteins that are Gα subunit selective and positive allosteric modulation and agonism for ß-arrestin translocation at NTSR1. Detailed structural analysis of the allosteric binding site illuminated the structural determinants for biased allosteric modulation of SBI-553 on NTSR1.

Ligand recognition and allosteric modulation of the human MRGPRX1 receptor.

The human MAS-related G protein-coupled receptor X1 (MRGPRX1) is preferentially expressed in the small-diameter primary sensory neurons and involved in the mediation of nociception and pruritus. Central activation of MRGPRX1 by the endogenous opioid peptide fragment BAM8-22 and its positive allosteric modulator ML382 has been shown to effectively inhibit persistent pain, making MRGPRX1 a promising target for non-opioid pain treatment. However, the activation mechanism of MRGPRX1 is still largely unknown. Here we report three high-resolution cryogenic electron microscopy structures of MRGPRX1-Gαq in complex with BAM8-22 alone, with BAM8-22 and ML382 simultaneously as well as with a synthetic agonist compound-16. These structures reveal the agonist binding mode for MRGPRX1 and illuminate the structural requirements for positive allosteric modulation. Collectively, our findings provide a molecular understanding of the activation and allosteric modulation of the MRGPRX1 receptor, which could facilitate the structure-based design of non-opioid pain-relieving drugs.

Molecular basis for selective activation of DREADD-based chemogenetics.

Designer receptors exclusively activated by designer drugs (DREADDs) represent a powerful chemogenetic technology for the remote control of neuronal activity and cellular signalling1-4. The muscarinic receptor-based DREADDs are the most widely used chemogenetic tools in neuroscience research. The Gq-coupled DREADD (hM3Dq) is used to enhance neuronal activity, whereas the Gi/o-coupled DREADD (hM4Di) is utilized to inhibit neuronal activity5. Here we report four DREADD-related cryogenic electron microscopy high-resolution structures: a hM3Dq-miniGq complex and a hM4Di-miniGo complex bound to deschloroclozapine; a hM3Dq-miniGq complex bound to clozapine-N-oxide; and a hM3R-miniGq complex bound to iperoxo. Complemented with mutagenesis, functional and computational simulation data, our structures reveal key details of the recognition of DREADD chemogenetic actuators and the molecular basis for activation. These findings should accelerate the structure-guided discovery of next-generation chemogenetic tools.

Bespoke library docking for 5-HT2A receptor agonists with antidepressant activity.

There is considerable interest in screening ultralarge chemical libraries for ligand discovery, both empirically and computationally1-4. Efforts have focused on readily synthesizable molecules, inevitably leaving many chemotypes unexplored. Here we investigate structure-based docking of a bespoke virtual library of tetrahydropyridines-a scaffold that is poorly sampled by a general billion-molecule virtual library but is well suited to many aminergic G-protein-coupled receptors. Using three inputs, each with diverse available derivatives, a one pot C-H alkenylation, electrocyclization and reduction provides the tetrahydropyridine core with up to six sites of derivatization5-7. Docking a virtual library of 75 million tetrahydropyridines against a model of the serotonin 5-HT2A receptor (5-HT2AR) led to the synthesis and testing of 17 initial molecules. Four of these molecules had low-micromolar activities against either the 5-HT2A or the 5-HT2B receptors. Structure-based optimization led to the 5-HT2AR agonists (R)-69 and (R)-70, with half-maximal effective concentration values of 41 nM and 110 nM, respectively, and unusual signalling kinetics that differ from psychedelic 5-HT2AR agonists. Cryo-electron microscopy structural analysis confirmed the predicted binding mode to 5-HT2AR. The favourable physical properties of these new agonists conferred high brain permeability, enabling mouse behavioural assays. Notably, neither had psychedelic activity, in contrast to classic 5-HT2AR agonists, whereas both had potent antidepressant activity in mouse models and had the same efficacy as antidepressants such as fluoxetine at as low as 1/40th of the dose. Prospects for using bespoke virtual libraries to sample pharmacologically relevant chemical space will be considered.

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.

Structural optimizations and bioevaluation of N-H aporphine analogues as Gq-biased and selective serotonin 5-HT2C receptor agonists.

The concept of subtype selectivity and functional bias has recently reshaped current GPCR drug discovery for G protein-coupled receptors. A series of new N-H aporphines with A-ring modifications have been synthesized, and their efficacy on 5-HT2 receptor activation was evaluated. SAR analysis led to the discovery of several more potent and selective 5-HT2C receptor agonists (e.g., 11b and 11f) with low nanomolar activity. Molecular docking analysis of this series of aporphines was in accordance with our SAR results. The functional selectivity of specific compounds was tested via both Gq-mediated calcium flux and ß-arrestin recruitment assays, which revealed that these compounds exhibited no ß-arrestin recruitment activity. Further ADMET study combined with behavioral assessment using a methamphetamine-induced hyperactivity model identified compound 11b and 11f possessing promising drug-like profiles and having antipsychotic potential. These agonists with an exclusive bias toward Gq signaling may serve as valuable pharmacological probes to facilitate the elucidation of therapeutically relevant 5-HT2C signaling pathways and the development of alternative antipsychotic medications.

Subversion of Serotonin Receptor Signaling in Osteoblasts by Kynurenine Drives Acute Myeloid Leukemia.

Remodeling of the microenvironment by tumor cells can activate pathways that favor cancer growth. Molecular delineation and targeting of such malignant-cell nonautonomous pathways may help overcome resistance to targeted therapies. Herein we leverage genetic mouse models, patient-derived xenografts, and patient samples to show that acute myeloid leukemia (AML) exploits peripheral serotonin signaling to remodel the endosteal niche to its advantage. AML progression requires the presence of serotonin receptor 1B (HTR1B) in osteoblasts and is driven by AML-secreted kynurenine, which acts as an oncometabolite and HTR1B ligand. AML cells utilize kynurenine to induce a proinflammatory state in osteoblasts that, through the acute-phase protein serum amyloid A (SAA), acts in a positive feedback loop on leukemia cells by increasing expression of IDO1-the rate-limiting enzyme for kynurenine synthesis-thereby enabling AML progression. This leukemia-osteoblast cross-talk, conferred by the kynurenine-HTR1B-SAA-IDO1 axis, could be exploited as a niche-focused therapeutic approach against AML, opening new avenues for cancer treatment. SIGNIFICANCE: AML remains recalcitrant to treatments due to the emergence of resistant clones. We show a leukemia-cell nonautonomous progression mechanism that involves activation of a kynurenine-HTR1B-SAA-IDO1 axis between AML cells and osteoblasts. Targeting the niche by interrupting this axis can be pharmacologically harnessed to hamper AML progression and overcome therapy resistance. This article is highlighted in the In This Issue feature, p. 873.

Synthon-based ligand discovery in virtual libraries of over 11 billion compounds.

Structure-based virtual ligand screening is emerging as a key paradigm for early drug discovery owing to the availability of high-resolution target structures1-4 and ultra-large libraries of virtual compounds5,6. However, to keep pace with the rapid growth of virtual libraries, such as readily available for synthesis (REAL) combinatorial libraries7, new approaches to compound screening are needed8,9. Here we introduce a modular synthon-based approach-V-SYNTHES-to perform hierarchical structure-based screening of a REAL Space library of more than 11 billion compounds. V-SYNTHES first identifies the best scaffold-synthon combinations as seeds suitable for further growth, and then iteratively elaborates these seeds to select complete molecules with the best docking scores. This hierarchical combinatorial approach enables the rapid detection of the best-scoring compounds in the gigascale chemical space while performing docking of only a small fraction (<0.1%) of the library compounds. Chemical synthesis and experimental testing of novel cannabinoid antagonists predicted by V-SYNTHES demonstrated a 33% hit rate, including 14 submicromolar ligands, substantially improving over a standard virtual screening of the Enamine REAL diversity subset, which required approximately 100 times more computational resources. Synthesis of selected analogues of the best hits further improved potencies and affinities (best inhibitory constant (Ki) = 0.9 nM) and CB2/CB1 selectivity (50-200-fold). V-SYNTHES was also tested on a kinase target, ROCK1, further supporting its use for lead discovery. The approach is easily scalable for the rapid growth of combinatorial libraries and potentially adaptable to any docking algorithm.