Limitations and potential of κOR biased agonists for pain and itch management.

The concept of ligand bias is based on the premise that different agonists can elicit distinct responses by selectively activating the same receptor. These responses often determine whether an agonist has therapeutic or undesirable effects. Therefore, it would be highly advantageous to have agonists that specifically trigger the therapeutic response. The last two decades have seen a growing trend towards the consideration of ligand bias in the development of ligands to target the κ-opioid receptor (κOR). Most of these ligands selectively favor G-protein signaling over ß-arrestin signaling to potentially provide effective pain and itch relief without adverse side effects associated with κOR activation. Importantly, the specific role of ß-arrestin 2 in mediating κOR agonist-induced side effects remains unknown, and similarly the therapeutic and side-effect profiles of G-protein-biased κOR agonists have not been established. Furthermore, some drugs previously labeled as G-protein-biased may not exhibit true bias but may instead be either low-intrinsic-efficacy or partial agonists. In this review, we discuss the established methods to test ligand bias, their limitations in measuring bias factors for κOR agonists, as well as recommend the consideration of other systematic factors to correlate the degree of bias signaling and pharmacological effects.

A µ-opioid receptor modulator that works cooperatively with naloxone.

The µ-opioid receptor (µOR) is a well-established target for analgesia1, yet conventional opioid receptor agonists cause serious adverse effects, notably addiction and respiratory depression. These factors have contributed to the current opioid overdose epidemic driven by fentanyl2, a highly potent synthetic opioid. µOR negative allosteric modulators (NAMs) may serve as useful tools in preventing opioid overdose deaths, but promising chemical scaffolds remain elusive. Here we screened a large DNA-encoded chemical library against inactive µOR, counter-screening with active, G-protein and agonist-bound receptor to 'steer' hits towards conformationally selective modulators. We discovered a NAM compound with high and selective enrichment to inactive µOR that enhances the affinity of the key opioid overdose reversal molecule, naloxone. The NAM works cooperatively with naloxone to potently block opioid agonist signalling. Using cryogenic electron microscopy, we demonstrate that the NAM accomplishes this effect by binding a site on the extracellular vestibule in direct contact with naloxone while stabilizing a distinct inactive conformation of the extracellular portions of the second and seventh transmembrane helices. The NAM alters orthosteric ligand kinetics in therapeutically desirable ways and works cooperatively with low doses of naloxone to effectively inhibit various morphine-induced and fentanyl-induced behavioural effects in vivo while minimizing withdrawal behaviours. Our results provide detailed structural insights into the mechanism of negative allosteric modulation of the µOR and demonstrate how this can be exploited in vivo.

Liver ACOX1 regulates levels of circulating lipids that promote metabolic health through adipose remodeling.

The liver gene expression of the peroxisomal ß-oxidation enzyme acyl-coenzyme A oxidase 1 (ACOX1), which catabolizes very long chain fatty acids (VLCFA), increases in the context of obesity, but how this pathway impacts systemic energy metabolism remains unknown. Here, we show that hepatic ACOX1-mediated ß-oxidation regulates inter-organ communication involved in metabolic homeostasis. Liver-specific knockout of Acox1 (Acox1-LKO) protects mice from diet-induced obesity, adipose tissue inflammation, and systemic insulin resistance. Serum from Acox1-LKO mice promotes browning in cultured white adipocytes. Global serum lipidomics show increased circulating levels of several species of ω-3 VLCFAs (C24-C28) with previously uncharacterized physiological role that promote browning, mitochondrial biogenesis and Glut4 translocation through activation of the lipid sensor GPR120 in adipocytes. This work identifies hepatic peroxisomal ß-oxidation as an important regulator of metabolic homeostasis and suggests that manipulation of ACOX1 or its substrates may treat obesity-associated metabolic disorders.

Searching for Synthetic Opioid Rescue Agents: Identification of a Potent Opioid Agonist with Reduced Respiratory Depression.

While in the process of designing more effective synthetic opioid rescue agents, we serendipitously identified a new chemotype of potent synthetic opioid. Here, we report that conformational constraint of a piperazine ring converts a mu opioid receptor (MOR) antagonist into a potent MOR agonist. The prototype of the series, which we have termed atoxifent (2), possesses potent in vitro agonist activity. In mice, atoxifent displayed long-lasting antinociception that was reversible with naltrexone. Repeated dosing of atoxifent produced antinociceptive tolerance and a level of withdrawal like that of fentanyl. In rats, while atoxifent produced complete loss of locomotor activity like fentanyl, it failed to produce deep respiratory depression associated with fentanyl-induced lethality. Assessment of brain biodistribution demonstrated ample distribution of atoxifent into the brain with a Tmax of approximately 0.25 h. These results indicate enhanced safety for atoxifent-like molecules compared to fentanyl.

High spatial resolution elevation change dataset derived from ICESat-2 crossover points on the Tibetan Plateau.

Understanding elevation changes on the Tibetan Plateau is crucial to comprehend the changes in topography, landscape, climate, environmental conditions, and water resources. However, some of the current products that track elevation changes only cover specific surface types or limited areas, and others have low spatial resolution. We propose an algorithm to extract ICESat-2 crossover points dataset for the Tibetan Plateau, and form a dataset. The crossover points dataset has a density of 2.015 groups/km², and each group of crossover points indicates the amount of change in elevation before and after a period of time over an area of approximately 17 meters in diameter. Comparing ICESat-2 crossover points data with existing studies on glaciers and lakes, we demonstrated the reliability of the derived elevation changes. The ICESat-2 crossover points provide a refined data source for understanding high-spatial-resolution elevation changes on the Tibetan Plateau. This dataset can provide validation data for various studies that require high-precision or high-resolution elevation change data on the Tibetan Plateau.

Ligand efficacy modulates conformational dynamics of the µ-opioid receptor.

The µ-opioid receptor (µOR) is an important target for pain management1 and molecular understanding of drug action on µOR will facilitate the development of better therapeutics. Here we show, using double electron-electron resonance and single-molecule fluorescence resonance energy transfer, how ligand-specific conformational changes of µOR translate into a broad range of intrinsic efficacies at the transducer level. We identify several conformations of the cytoplasmic face of the receptor that interconvert on different timescales, including a pre-activated conformation that is capable of G-protein binding, and a fully activated conformation that markedly reduces GDP affinity within the ternary complex. Interaction of ß-arrestin-1 with the µOR core binding site appears less specific and occurs with much lower affinity than binding of Gi.

Extreme low air temperature and reduced moisture jointly inhibit respiration in alpine grassland on the Qinghai-Tibetan Plateau.

Alpine grassland is the main vegetation on the Qinghai-Tibetan Plateau (QTP) and exhibits high sensitivity to extreme weather events. With global warming, extreme weather events are projected to become more frequent on the QTP. However, the impact of these extreme weather events on the carbon cycle of alpine grassland remains unclear. The long-term in-situ carbon fluxes data was collected from 2013 to 2022 at an alpine grassland site to examine the impact of extreme low air temperature (ELT) and reduced moisture (including air and soil) on carbon fluxes during the growing season. Our findings indicated that a significant increase in net ecosystem production (NEP) after 2019, with the average NEP increasing from 278.91 ± 43.27 g C m-2 year-1 during 2013-2018 to 415.45 ± 45.29 g C m-2 year-1 during 2019-2022. The ecosystem carbon use efficiency (CUE) increased from 0.38 ± 0.06 during 2013-2018 to 0.62 ± 0.11 during 2019-2022. By combining concurrently measured environmental factors and remote sensing data, we identified the factors responsible for the abrupt change in the NEP after 2019. This phenomenon was caused by an abrupt decrease in ecosystem respiration (Reco) after 2019, which resulted from the inhibition imposed by ELT and reduced moisture. In contrast, gross primary production (GPP) remained stable from 2013 to 2022, which was confirmed by the remotely sensed vegetation index. This study highlights that combined extreme weather events associated with climate change can significantly impact the NEP of alpine grassland, potentially affecting different carbon fluxes at different rates. These findings provide new insights into the mechanisms governing the carbon cycle of alpine grassland.

GPCR-G protein selectivity revealed by structural pharmacology.

Receptor-G protein promiscuity is frequently observed in class A G protein-coupled receptors (GPCRs). In particular, GPCRs can couple with G proteins from different families (Gαs, Gαq/11, Gαi/o, and Gα12/13) or the same family subtypes. The molecular basis underlying the selectivity/promiscuity is not fully revealed. We recently reported the structures of kappa opioid receptor (KOR) in complex with the Gi/o family subtypes [Gαi1, GαoA, Gαz, and Gustducin (Gαg)] determined by cryo-electron microscopy (cryo-EM). The structural analysis, in combination with pharmacological studies, provides insights into Gi/o subtype selectivity. Given the conserved sequence identity and activation mechanism between different G protein families, the findings within Gi/o subtypes could be likely extended to other families. Understanding the KOR-Gi/o or GPCR-G protein selectivity will facilitate the development of more precise therapeutics targeting a specific G protein subtype.

Design and structural validation of peptide-drug conjugate ligands of the kappa-opioid receptor.

Despite the increasing number of GPCR structures and recent advances in peptide design, the development of efficient technologies allowing rational design of high-affinity peptide ligands for single GPCRs remains an unmet challenge. Here, we develop a computational approach for designing conjugates of lariat-shaped macrocyclized peptides and a small molecule opioid ligand. We demonstrate its feasibility by discovering chemical scaffolds for the kappa-opioid receptor (KOR) with desired pharmacological activities. The designed De Novo Cyclic Peptide (DNCP)-ß-naloxamine (NalA) exhibit in vitro potent mixed KOR agonism/mu-opioid receptor (MOR) antagonism, nanomolar binding affinity, selectivity, and efficacy bias at KOR. Proof-of-concept in vivo efficacy studies demonstrate that DNCP-ß-NalA(1) induces a potent KOR-mediated antinociception in male mice. The high-resolution cryo-EM structure (2.6 Å) of the DNCP-ß-NalA-KOR-Gi1 complex and molecular dynamics simulations are harnessed to validate the computational design model. This reveals a network of residues in ECL2/3 and TM6/7 controlling the intrinsic efficacy of KOR. In general, our computational de novo platform overcomes extensive lead optimization encountered in ultra-large library docking and virtual small molecule screening campaigns and offers innovation for GPCR ligand discovery. This may drive the development of next-generation therapeutics for medical applications such as pain conditions.

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.

Molecular basis of opioid receptor signaling.

Opioids are used for pain management despite the side effects that contribute to the opioid crisis. The pursuit of non-addictive opioid analgesics remains unattained due to the unresolved intricacies of opioid actions, receptor signaling cascades, and neuronal plasticity. Advancements in structural, molecular, and computational tools illuminate the dynamic interplay between opioids and opioid receptors, as well as the molecular determinants of signaling pathways, which are potentially interlinked with pharmacological responses. Here, we review the molecular basis of opioid receptor signaling with a focus on the structures of opioid receptors bound to endogenous peptides or pharmacological agents. These insights unveil specific interactions that dictate ligand selectivity and likely their distinctive pharmacological profiles. Biochemical analysis further unveils molecular features governing opioid receptor signaling. Simultaneously, the synergy between computational biology and medicinal chemistry continues to expedite the discovery of novel chemotypes with the promise of yielding more efficacious and safer opioid compounds.

Enhancing Leaf Area Index Estimation for Maize with Tower-Based Multi-Angular Spectral Observations.

The leaf area index (LAI) played a crucial role in ecological, hydrological, and climate models. The normalized difference vegetation index (NDVI) has been a widely used tool for LAI estimation. However, the NDVI quickly saturates in dense vegetation and is susceptible to soil background interference in sparse vegetation. We proposed a multi-angular NDVI (MAVI) to enhance LAI estimation using tower-based multi-angular observations, aiming to minimize the interference of soil background and saturation effects. Our methodology involved collecting continuous tower-based multi-angular reflectance and the LAI over a three-year period in maize cropland. Then we proposed the MAVI based on an analysis of how canopy reflectance varies with solar zenith angle (SZA). Finally, we quantitatively evaluated the MAVI's performance in LAI retrieval by comparing it to eight other vegetation indices (VIs). Statistical tests revealed that the MAVI exhibited an improved curvilinear relationship with the LAI when the NDVI is corrected using multi-angular observations (R2 = 0.945, RMSE = 0.345, rRMSE = 0.147). Furthermore, the MAVI-based model effectively mitigated soil background effects in sparse vegetation (R2 = 0.934, RMSE = 0.155, rRMSE = 0.157). Our findings demonstrated the utility of tower-based multi-angular spectral observations in LAI retrieval, having the potential to provide continuous data for validating space-borne LAI products. This research significantly expanded the potential applications of multi-angular observations.

An RFI-suppressed SMOS L-band multi-angular brightness temperature dataset spanning over a decade (since 2010).

The Soil Moisture Ocean Salinity (SMOS) was the first mission providing L-band multi-angular brightness temperature (TB) at the global scale. However, radio frequency interferences (RFI) and aliasing effects degrade, when present SMOS TBs, and thus affect the retrieval of land parameters. To alleviate this, a refined SMOS multi-angular TB dataset was generated based on a two-step regression approach. This approach smooths the TBs and reconstructs data at the incidence angle with large TB uncertainties. Compared with Centre Aval de Traitement des Données SMOS (CATDS) TB product, this dataset shows a better relationship with the Soil Moisture Active Passive (SMAP) TB and enhanced correlation with in-situ measured soil moisture. This RFI-suppressed SMOS TB dataset, spanning more than a decade (since 2010), is expected to provide opportunities for better retrieval of land parameters and scientific applications.

Direct Selection of DNA-Encoded Libraries for Biased Agonists of GPCRs on Live Cells.

G protein-coupled receptors (GPCRs) are the largest superfamily of human membrane target proteins for approved drugs. GPCR ligands can have a complex array of pharmacological activities. Among these activities, biased agonists have potential to serve as both chemical probes to understand specific aspects of receptor signaling and therapeutic leads with more specific, desired activity. Challenges exist, however, in the development of new biased activators due, in part, to the low throughput of traditional screening approaches. DNA-encoded chemical libraries (DELs) dramatically improve the throughput of drug discovery by allowing a collective selection, rather than discrete screening, of large compound libraries. The use of DELs has been largely limited to affinity-based selections against purified protein targets, which identify binders only. Herein, we report a split protein complementation approach that allows direct identification of DNA-linked molecules that induce the dimerization of two proteins. We used this selection with a DEL against opioid receptor GPCRs on living cells for the identification of small molecules that possess the specific function of activation of either ß-arrestin or G protein signaling pathways. This approach was applied to δ-, µ-, and κ-opioid receptors and enabled the discovery of compound [66,66], a selective, G-protein-biased agonist of the κ-opioid receptor (EC50 = 100 nM, E max = 82%, Gi bias factor = 6.6). This approach should be generally applicable for the direct selection of chemical inducers of dimerization from DELs and expand the utility of DELs to enrich molecules with a specific and desired biochemical function.

Conformational dynamics of the µ-opioid receptor determine ligand intrinsic efficacy.

The µ-opioid receptor (µOR) is an important target for pain management and the molecular understanding of drug action will facilitate the development of better therapeutics. Here we show, using double electron-electron resonance (DEER) and single-molecule fluorescence resonance energy transfer (smFRET), how ligand-specific conformational changes of the µOR translate into a broad range of intrinsic efficacies at the transducer level. We identify several cytoplasmic receptor conformations interconverting on different timescales, including a pre-activated receptor conformation which is capable of G protein binding, and a fully activated conformation which dramatically lowers GDP affinity within the ternary complex. Interaction of ß-arrestin-1 with the µOR core binding site appears less specific and occurs with much lower affinity than binding of G protein Gi.

Ligand and G-protein selectivity in the κ-opioid receptor.

The κ-opioid receptor (KOR) represents a highly desirable therapeutic target for treating not only pain but also addiction and affective disorders1. However, the development of KOR analgesics has been hindered by the associated hallucinogenic side effects2. The initiation of KOR signalling requires the Gi/o-family proteins including the conventional (Gi1, Gi2, Gi3, GoA and GoB) and nonconventional (Gz and Gg) subtypes. How hallucinogens exert their actions through KOR and how KOR determines G-protein subtype selectivity are not well understood. Here we determined the active-state structures of KOR in a complex with multiple G-protein heterotrimers-Gi1, GoA, Gz and Gg-using cryo-electron microscopy. The KOR-G-protein complexes are bound to hallucinogenic salvinorins or highly selective KOR agonists. Comparisons of these structures reveal molecular determinants critical for KOR-G-protein interactions as well as key elements governing Gi/o-family subtype selectivity and KOR ligand selectivity. Furthermore, the four G-protein subtypes display an intrinsically different binding affinity and allosteric activity on agonist binding at KOR. These results provide insights into the actions of opioids and G-protein-coupling specificity at KOR and establish a foundation to examine the therapeutic potential of pathway-selective agonists of KOR.

Molecular mechanism of biased signaling at the kappa opioid receptor.

The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.

Structure-based design of bitopic ligands for the µ-opioid receptor.

Mu-opioid receptor (µOR) agonists such as fentanyl have long been used for pain management, but are considered a major public health concern owing to their adverse side effects, including lethal overdose1. Here, in an effort to design safer therapeutic agents, we report an approach targeting a conserved sodium ion-binding site2 found in µOR3 and many other class A G-protein-coupled receptors with bitopic fentanyl derivatives that are functionalized via a linker with a positively charged guanidino group. Cryo-electron microscopy structures of the most potent bitopic ligands in complex with µOR highlight the key interactions between the guanidine of the ligands and the key Asp2.50 residue in the Na+ site. Two bitopics (C5 and C6 guano) maintain nanomolar potency and high efficacy at Gi subtypes and show strongly reduced arrestin recruitment-one (C6 guano) also shows the lowest Gz efficacy among the panel of µOR agonists, including partial and biased morphinan and fentanyl analogues. In mice, C6 guano displayed µOR-dependent antinociception with attenuated adverse effects, supporting the µOR sodium ion-binding site as a potential target for the design of safer analgesics. In general, our study suggests that bitopic ligands that engage the sodium ion-binding pocket in class A G-protein-coupled receptors can be designed to control their efficacy and functional selectivity profiles for Gi, Go and Gz subtypes and arrestins, thus modulating their in vivo pharmacology.

Insights into distinct signaling profiles of the µOR activated by diverse agonists.

Drugs targeting the µ-opioid receptor (µOR) are the most effective analgesics available but are also associated with fatal respiratory depression through a pathway that remains unclear. Here we investigated the mechanistic basis of action of lofentanil (LFT) and mitragynine pseudoindoxyl (MP), two µOR agonists with different safety profiles. LFT, one of the most lethal opioids, and MP, a kratom plant derivative with reduced respiratory depression in animal studies, exhibited markedly different efficacy profiles for G protein subtype activation and ß-arrestin recruitment. Cryo-EM structures of µOR-Gi1 complex with MP (2.5 Å) and LFT (3.2 Å) revealed that the two ligands engage distinct subpockets, and molecular dynamics simulations showed additional differences in the binding site that promote distinct active-state conformations on the intracellular side of the receptor where G proteins and ß-arrestins bind. These observations highlight how drugs engaging different parts of the µOR orthosteric pocket can lead to distinct signaling outcomes.