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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Structure determination of inactive-state GPCRs with a universal nanobody.

Cryogenic electron microscopy (cryo-EM) has widened the field of structure-based drug discovery by allowing for routine determination of membrane protein structures previously intractable. Despite representing one of the largest classes of therapeutic targets, most inactive-state G protein-coupled receptors (GPCRs) have remained inaccessible for cryo-EM because their small size and membrane-embedded nature impedes projection alignment for high-resolution map reconstructions. Here we demonstrate that the same single-chain camelid antibody (nanobody) recognizing a grafted intracellular loop can be used to obtain cryo-EM structures of inactive-state GPCRs at resolutions comparable or better than those obtained by X-ray crystallography. Using this approach, we obtained structures of neurotensin 1 receptor bound to antagonist SR48692, µ-opioid receptor bound to alvimopan, apo somatostatin receptor 2 and histamine receptor 2 bound to famotidine. We expect this rapid, straightforward approach to facilitate the broad exploration of GPCR inactive states without the need for extensive engineering and crystallization.

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.

Satellite-Enabled Internet of Remote Things Network Transmits Field Data from the Most Remote Areas of the Tibetan Plateau.

In this article, we employed a satellite-enabled Internet of Remote Things (IoRT) network as a promising solution to retrieve data in the most remote areas of interest, where public networks are absent. This article presents a system network based on the satellite-enabled IoRT, a new paradigm that defines a network where each environmental monitoring device can autonomously establish a network with a remote data center. The Xingyun satellite constellation was employed for data retrieval on the Tibetan Plateau (TP). The monitoring system was mainly composed of a ground Internet of Things (IoT) terminal that was built with satellite transceivers, environmental monitoring devices, and system software. We deployed five of these newly developed terminals in harsh areas to monitor environmental variables, and accordingly, air temperature and relative humidity, precipitation, snow depth, land surface temperature, tree stemflow rate, and photosynthetically active radiation were retrieved with the satellite-enabled IoRT network. Field experiments were conducted to evaluate the performance of the proposed system network, and the results indicated that the average time delay with and without the packet creation mode reached 32 and 32.7 s, respectively, and the average packet loss rate with and without the packet creation mode reached 5.63% and 4.48%, respectively. The successful implementation of the satellite-enabled IoRT network for the rapid retrieval of monitoring data in remote glacier, forestland, and canyon areas at very high altitudes on the TP provides an entirely new and revolutionary data retrieval means for backhauling data from remote areas of interest.

Spotlight on Nociceptin/Orphanin FQ Receptor in the Treatment of Pain.

In our society today, pain has become a main source of strain on most individuals. It is crucial to develop novel treatments against pain while focusing on decreasing their adverse effects. Throughout the extent of development for new pain therapies, the nociceptin/orphanin FQ receptor (NOP receptor) has appeared to be an encouraging focal point. Concentrating on NOP receptor to treat chronic pain with limited range of unwanted effects serves as a suitable alternative to prototypical opioid morphine that could potentially lead to life-threatening effects caused by respiratory depression in overdose, as well as generate abuse and addiction. In addition to these harmful effects, the uprising opioid epidemic is responsible for becoming one of the most disastrous public health issues in the US. In this article, the contributing molecular and cellular structure in controlling the cellular trafficking of NOP receptor and studies that support the role of NOP receptor and its ligands in pain management are reviewed.