Elucidating the active δ-opioid receptor crystal structure with peptide and small-molecule agonists

Structure-guided design of partial agonists at an opioid receptor

Chronic pain and opioid overdose deaths highlight the need for non-addictive analgesics with novel mechanisms. The δ opioid receptor (δOR) is a promising target, as it lacks the respiratory depression associated with µ opioid receptor (µOR) agonists. However, early δOR full agonists caused seizures, limiting their clinical use. Partial δOR agonists may offer more controlled receptor activation than full agonists, but their development has been hindered by uncertainty regarding the molecular mechanism of partial agonism. Here we show that C6-Quino, a bitopic ligand developed through structure-based design, acts as a selective δOR partial agonist. Functional studies reveal that C6-Quino shows differential activity at G-protein and arrestin pathways and interacts with the sodium binding pocket, confirmed through cryo-EM analysis. C6-Quino demonstrates oral activity, analgesic activity in chronic pain models without causing δOR-related seizures and µOR-related adverse effects which have limited opioid usage in recent times. This discovery outlines a new strategy for developing δOR-targeted analgesics and provides a framework for optimizing signaling profiles of other Class A GPCRs.

OpenMMDL - Simplifying the Complex: Building, Simulating, and Analyzing Protein-Ligand Systems in OpenMM

Molecular dynamics (MD) simulations have become an essential tool for studying the dynamics of biological systems and exploring protein-ligand interactions. OpenMM is a modern, open-source software toolkit designed for MD simulations. Until now, it has lacked a module dedicated to building receptor-ligand systems, which is highly useful for investigating protein-ligand interactions for drug discovery. We therefore introduce OpenMMDL, an open-source toolkit that enables the preparation and simulation of protein-ligand complexes in OpenMM, along with the subsequent analysis of protein-ligand interactions. OpenMMDL consists of three main components: OpenMMDL Setup, a graphical user interface based on Python Flask to prepare protein and simulation settings, OpenMMDL Simulation to perform MD simulations with consecutive trajectory postprocessing, and finally OpenMMDL Analysis to analyze simulation results with respect to ligand binding. OpenMMDL is not only a versatile tool for analyzing protein-ligand interactions and generating ligand binding modes throughout simulations; it also tracks and clusters water molecules, particularly those exhibiting minimal displacement from their previous coordinates, providing insights into solvent dynamics. We applied OpenMMDL to study ligand-receptor interactions across diverse biological systems, including LDN-193189 and LDN-212854 with ALK2 (kinases), nifedipine and amlodipine in Cav1.1 (ion channels), LSD in 5-HT2B (G-protein coupled receptors), letrozole in CYP19A1 (cytochrome P450 oxygenases), flavin mononucleotide binding the FMN-riboswitch (RNAs), ligand C08 bound to TLR8 (toll-like receptor), and PZM21 bound to MOR (opioid receptor), highlighting distinct functionalities of OpenMMDL. OpenMMDL is publicly available at https://github.com/wolberlab/OpenMMDL.

A combined in silico approach to design peptide ligands with increased receptor-subtype selectivity

G-protein coupled receptors are major drug targets that change their conformation upon binding of ligands to their extracellular binding pocket to transduce the signal to intracellular G-proteins or arrestins. In drug screening campaigns, computational methods are frequently used to predict binding affinities for chemical compounds in silico before experimental testing. Some of these methods take into consideration the inherent flexibility of the ligand and to some extent also of the receptor. Due to high structural flexibility, peptide ligands are exceptionally difficult to handle and approaches to effectively sample in silico receptor-peptide ligand interactions are limited. Here we describe a pipeline starting from microseconds molecular dynamics simulations of receptor and receptor ligand complexes to find reasonable starting conformations and derive constraints for subsequent flexible docking of peptide ligands, using Rosetta's FlexPepDock approach. We applied this approach to predict binding affinities for dynorphin and its variants to members of the opioid receptor family. Using an ensemble of docking poses, Rosetta's fixbb protein design method explored the sequence space at defined positions, to enhance binding affinities, aiming to increase subtype selectivity towards κ-opioid receptor while decreasing it towards μ-opioid receptor. The results of our computations were validated experimentally in a related study (Zangrandi et al., 2024[1]). Four out of six proposed variants lead to a significant increase in subtype selectivity in favor of κ-opioid receptor, highlighting the potential of our approach to design subtype selective peptide variants. The established workflow may also apply for other receptor types activated by peptide ligands.

Intracellular Pocket Conformations Determine Signaling Efficacy through the μ Opioid Receptor

It has been challenging to determine how a ligand that binds to a receptor activates downstream signaling pathways and to predict the strength of signaling. The challenge is compounded by functional selectivity, in which a single ligand binding to a single receptor can activate multiple signaling pathways at different levels. Spectroscopic studies show that in the largest class of cell surface receptors, 7 transmembrane receptors (7TMRs), activation is associated with ligand-induced shifts in the equilibria of intracellular pocket conformations in the absence of transducer proteins. We hypothesized that signaling through the μ opioid receptor, a prototypical 7TMR, is linearly proportional to the equilibrium probability of observing intracellular pocket conformations in the receptor-ligand complex. Here, we show that a machine learning model based on this hypothesis accurately calculates the efficacy of both G protein and β-arrestin-2 signaling. Structural features that the model associates with activation are intracellular pocket expansion, toggle switch rotation, and sodium binding pocket collapse. Distinct pathways are activated by different arrangements of the ligand and sodium binding pockets and the intracellular pocket. While recent work has categorized ligands as active or inactive (or partially active) based on binding affinities to two conformations, our approach accurately computes signaling efficacy along multiple pathways.

Structure-Signal Relationships of the δ-Opioid-Receptor (DOR)-Selective Agonist KNT-127-Part I: Impact of the Morphinan Skeleton on the G-Protein-Biased DOR Agonism

The δ-opioid receptor (DOR) is a promising target for developing novel analgesics due to its lower risk of causing side effects compared to the μ-opioid receptor (MOR), which is commonly associated with dependence, respiratory depression, and other adverse effects. KNT-127, a DOR-selective agonist with a morphinan skeleton, offers analgesic and antidepressant benefits without inducing convulsions at therapeutic doses, unlike the conventional DOR agonist SNC80. While previous studies have suggested that KNT-127 exhibits reduced β-arrestin recruitment, a signaling pathway implicated in adverse opioid effects, the ligand structural basis for this biased signaling remains unclear. In this study, we explored the structure-signal relationships of KNT-127, focusing on its quinoline moiety, which is known to serve as an address domain responsible for DOR selectivity. Modifying the quinoline moiety by removing the aromatic rings reduced DOR selectivity and potency in relation to G-protein activation while diminishing both the potency and efficacy of β-arrestin recruitment. These results suggest that the morphinan skeleton is critical for reduced β-arrestin recruitment, while the quinoline moiety differentially modulates G-protein activation and β-arrestin recruitment. Together, our study expands the message-address concept, previously limited to receptor selectivity, by providing structural insights into the G-protein-biased agonism of DOR agonists, thereby guiding the design of safer DOR-targeting therapeutics.

Insights into the interaction between hemorphins and δ-opioid receptor from molecular modeling

Hemorphins are short atypical opioid peptide fragments embedded in the β-chain of hemoglobin. They have received considerable attention recently due to their interaction with opioid receptors. The affinity of hemorphins to opioid receptors μ-opioid receptor (MOR), δ-opioid receptor (DOR), and κ-opioid receptor (KOR) has been well established. However, the underlying binding mode and molecular interactions of hemorphins in opioid receptors remain largely unknown. Here, we report the pattern of interaction of camel and other mammalian hemorphins with DOR. Extensive in silico docking and molecular dynamics simulations were employed to identify intermolecular interactions and binding energies were calculated to determine the affinity of these peptides for DOR. Longer forms of hemorphins - hemorphin-7, hemorphin-6, camel hemorphin-7, and camel hemorphin-6 had strong interactions with DOR. However, camel hemorphin-7 and camel hemorphin-6 had high binding affinity towards DOR. Thus, the findings of this study provide molecular insights into how hemorphins, particularly camel hemorphin variants, could be a therapeutic agent for pain regulation, stress management, and analgesia.

Intracellular pocket conformations determine signaling efficacy through the μ opioid receptor

It has been challenging to determine how a ligand that binds to a receptor activates downstream signaling pathways and to predict the strength of signaling. The challenge is compounded by functional selectivity, in which a single ligand binding to a single receptor can activate multiple signaling pathways at different levels. Spectroscopic studies show that in the largest class of cell surface receptors, 7 transmembrane receptors (7TMRs), activation is associated with ligand-induced shifts in the equilibria of intracellular pocket conformations in the absence of transducer proteins. We hypothesized that signaling through the μ opioid receptor, a prototypical 7TMR, is linearly proportional to the equilibrium probability of observing intracellular pocket conformations in the receptor-ligand complex. Here we show that a machine learning model based on this hypothesis accurately calculates the efficacy of both G protein and β -arrestin-2 signaling. Structural features that the model associates with activation are intracellular pocket expansion, toggle switch rotation, and sodium binding pocket collapse. Distinct pathways are activated by different arrangements of the ligand and sodium binding pockets and the intracellular pocket. While recent work has categorized ligands as active or inactive (or partially active) based on binding affinities to two conformations, our approach accurately computes signaling efficacy along multiple pathways.

Bivalent and bitopic ligands of the opioid receptors: The prospects of a dual approach

Opioid receptors belonging to the class A G-protein coupled receptors (GPCRs) are the targets of choice in the treatment of acute and chronic pain. However, their on-target side effects such as respiratory depression, tolerance and addiction have led to the advent of the 'opioid crisis'. In the search for safer analgesics, bivalent and more recently, bitopic ligands have emerged as valuable tool compounds to probe these receptors. The activity of bivalent and bitopic ligands rely greatly on the allosteric nature of the GPCRs. Bivalent ligands consist of two pharmacophores, each binding to the individual orthosteric binding site (OBS) of the monomers within a dimer. Bitopic or dualsteric ligands bridge the gap between the OBS and the spatially distinct, less conserved allosteric binding site (ABS) through the simultaneous occupation of these two sites. Bivalent and bitopic ligands stabilize distinct conformations of the receptors which ultimately translates into unique signalling and pharmacological profiles. Some of the interesting properties shown by these ligands include improved affinity and/or efficacy, subtype and/or functional selectivity and reduced side effects. This review aims at providing an overview of some of the bivalent and bitopic ligands of the opioid receptors and, their pharmacology in the hope of inspiring the design and discovery of the next generation of opioid analgesics.

Cryo-EM structure of small-molecule agonist bound delta opioid receptor-Gi complex enables discovery of biased compound

Delta opioid receptor (δOR) plays a pivotal role in modulating human sensation and emotion. It is an attractive target for drug discovery since, unlike Mu opioid receptor, it is associated with low risk of drug dependence. Despite its potential applications, the pharmacological properties of δOR, including the mechanisms of activation by small-molecule agonists and the complex signaling pathways it engages, as well as their relation to the potential side effects, remain poorly understood. In this study, we use cryo-electron microscopy (cryo-EM) to determine the structure of the δOR-Gi complex when bound to a small-molecule agonist (ADL5859). Moreover, we design a series of probes to examine the key receptor-ligand interaction site and identify a region involved in signaling bias. Using ADL06 as a chemical tool, we elucidate the relationship between the β-arrestin pathway of the δOR and its biological functions, such as analgesic tolerance and convulsion activities. Notably, we discover that the β-arrestin recruitment of δOR might be linked to reduced gastrointestinal motility. These insights enhance our understanding of δOR's structure, signaling pathways, and biological functions, paving the way for the structure-based drug discovery.

Identification of Cytisine Derivatives as Agonists of the Human Delta Opioid Receptor by Supercomputer-Based Virtual Drug Screening and Transcriptomics

Delta opioid receptors (DORs) are rising as therapeutic targets, not only for the treatment of pain but also other neurological disorders (e.g., Parkinson's disease). The advantage of DOR agonists compared to μ-opioid receptor agonists is that they have fewer side effects and a lower potential to induce tolerance. However, although multiple candidates have been tested in the past few decades, none have been approved for clinical use. The current study focused on searching for new DOR agonists by screening a chemical library containing 40,000 natural and natural-derived products. The functional activity of the top molecules was evaluated in vitro through the cyclic adenosine monophosphate accumulation assay. Compound 3 showed promising results, and its activity was further investigated through transcriptomic methods. Compound 3 inhibited the expression of TNF-α, prevented NF-κB translocation to the nucleus, and activated the G-protein-mediated ERK1/2 pathway. Additionally, compound 3 is structurally different from known DOR agonists, making it a valuable candidate for further investigation for its anti-inflammatory and analgesic potential.

Design, Synthesis, and In Vitro Characterization of Proteolytically-Stable Opioid-Neurotensin Hybrid Peptidomimetics

Linking an opioid to a nonopioid pharmacophore represents a promising approach for reducing opioid-induced side effects during pain management. Herein, we describe the optimization of the previously reported opioid-neurotensin hybrids (OPNT-hybrids), SBL-OPNT-05 & -10, containing the μ-/δ-opioid agonist H-Dmt-d-Arg-Aba-β-Ala-NH2 and NT(8-13) analogs optimized for NTS2 affinity. In the present work, the constrained dipeptide Aba-β-Ala was modified to investigate the optimal linker length between the two pharmacophores, as well as the effect of expanding the aromatic moiety within constrained dipeptide analogs, via the inclusion of a naphthyl moiety. Additionally, the N-terminal Arg residue of the NT(8-13) pharmacophore was substituted with β3 hArg. For all analogs, affinity was determined at the MOP, DOP, NTS1, and NTS2 receptors. Several of the hybrid ligands showed a subnanomolar affinity for MOP, improved binding for DOP compared to SBL-OPNT-05 & -10, as well as an excellent NTS2-affinity with high selectivity over NTS1. Subsequently, the Gαi1 and β-arrestin-2 pathways were evaluated for all hybrids, along with their stability in rat plasma. Upon MOP activation, SBL-OPNT-13 and -18 were the least effective at recruiting β-arrestin-2 (E max = 17 and 12%, respectively), while both compounds were also found to be partial agonists at the Gαi1 pathway, despite improved potency compared to DAMGO. Importantly, these analogs also showed a half-life in rat plasma in excess of 48 h, making them valuable tools for future in vivo investigations.

Enkephalins and Pain Modulation: Mechanisms of Action and Therapeutic Perspectives

Enkephalins, a subclass of endogenous opioid peptides, play a pivotal role in pain modulation. Enkephalins primarily exert their effects through opioid receptors located widely throughout both the central and peripheral nervous systems. This review will explore the mechanisms by which enkephalins produce analgesia, emotional regulation, neuroprotection, and other physiological effects. Furthermore, this review will analyze the involvement of enkephalins in the modulation of different pathologies characterized by severe pain. Understanding the complex role of enkephalins in pain processing provides valuable insight into potential therapeutic strategies for managing pain disorders.

Structure-Guided Design of Partial Agonists at an Opioid Receptor

The persistence of chronic pain and continuing overdose deaths from pain-relieving opioids targeting μ opioid receptor (μOR) have fueled the need for reliable long-term analgesics which use different targets and mechanisms. The δ opioid receptor (δOR) is a potential alternative target for non-addictive analgesics to alleviate chronic pain, made more attractive by its lack of respiratory depression associated with μOR agonists. However, early δOR full agonists were found to induce seizures, precluding clinical use. Partial δOR agonists may offer more controlled activation of the receptor compared to full agonists, but the development of such ligands has been hindered by uncertainty over the molecular mechanism mediating partial agonism. Using a structure-based approach, we explored the engagement of the sodium binding pocket in δOR and developed a bitopic ligand, C6-Quino, predicted to be a selective δOR partial agonist. Functional studies of C6-Quino revealed that it displayed δOR partial agonist activity at both G-protein and arrestin pathways. Its interaction with the sodium pocket was confirmed and analyzed using a single particle cryo-EM. Additionally, C6-Quino demonstrated favorable chemical and physiological properties like oral activity, and analgesic activity in multiple chronic pain models. Notably, μOR-related hyperlocomotion and respiratory depression, and δOR-related convulsions, were not observed at analgesic doses of C6-Quino. This fundamentally new approach to designing δOR ligands provides a blueprint for the development of partial agonists as safe analgesics and acts as a generic method to optimize signaling profiles of other Class A GPCRs.

Descriptive molecular pharmacology of the δ opioid receptor (DOR): A computational study with structural approach

This work focuses on the δ receptor (DOR), a G protein-coupled receptor (GPCR) belonging to the opioid receptor group. DOR is expressed in numerous tissues, particularly within the nervous system. Our study explores computationally the receptor's interactions with various ligands, including opiates and opioid peptides. It elucidates how these interactions influence the δ receptor response, relevant in a wide range of health and pathological processes. Thus, our investigation aims to explore the significance of DOR as an incoming drug target for pain relief and neurodegenerative diseases and as a source for novel opioid non-narcotic analgesic alternatives. We analyze the receptor's structural properties and interactions using Molecular Dynamics (MD) simulations and Gaussian-accelerated MD across different functional states. To thoroughly assess the primary differences in the structural and conformational ensembles across our different simulated systems, we initiated our study with 1 μs of conventional Molecular Dynamics. The strategy was chosen to encompass the full activation cycle of GPCRs, as activation processes typically occur within this microsecond range. Following the cMD, we extended our study with an additional 100 ns of Gaussian accelerated Molecular Dynamics (GaMD) to enhance the sampling of conformational states. This simulation approach allowed us to capture a comprehensive range of dynamic interactions and conformational changes that are crucial for GPCR activation as influenced by different ligands. Our study includes comparing agonist and antagonist complexes to uncover the collective patterns of their functional states, regarding activation, blocking, and inactivation of DOR, starting from experimental data. In addition, we also explored interactions between agonist and antagonist molecules from opiate and opioid classifications to establish robust structure-activity relationships. These interactions have been systematically quantified using a Quantitative Structure-Activity Relationships (QSAR) model. This research significantly contributes to our understanding of this significant pharmacological target, which is emerging as an attractive subject for drug development.

G Protein-Coupled Receptor-Ligand Pose and Functional Class Prediction

G protein-coupled receptor (GPCR) transmembrane protein family members play essential roles in physiology. Numerous pharmaceuticals target GPCRs, and many drug discovery programs utilize virtual screening (VS) against GPCR targets. Improvements in the accuracy of predicting new molecules that bind to and either activate or inhibit GPCR function would accelerate such drug discovery programs. This work addresses two significant research questions. First, do ligand interaction fingerprints provide a substantial advantage over automated methods of binding site selection for classical docking? Second, can the functional status of prospective screening candidates be predicted from ligand interaction fingerprints using a random forest classifier? Ligand interaction fingerprints were found to offer modest advantages in sampling accurate poses, but no substantial advantage in the final set of top-ranked poses after scoring, and, thus, were not used in the generation of the ligand-receptor complexes used to train and test the random forest classifier. A binary classifier which treated agonists, antagonists, and inverse agonists as active and all other ligands as inactive proved highly effective in ligand function prediction in an external test set of GPR31 and TAAR2 candidate ligands with a hit rate of 82.6% actual actives within the set of predicted actives.

Decoding the κ Opioid Receptor (KOR): Advancements in Structural Understanding and Implications for Opioid Analgesic Development

The opioid crisis in the United States is a significant public health issue, with a nearly threefold increase in opioid-related fatalities between 1999 and 2014. In response to this crisis, society has made numerous efforts to mitigate its impact. Recent advancements in understanding the structural intricacies of the κ opioid receptor (KOR) have improved our knowledge of how opioids interact with their receptors, triggering downstream signaling pathways that lead to pain relief. This review concentrates on the KOR, offering crucial structural insights into the binding mechanisms of both agonists and antagonists to the receptor. Through comparative analysis of the atomic details of the binding site, distinct interactions specific to agonists and antagonists have been identified. These insights not only enhance our understanding of ligand binding mechanisms but also shed light on potential pathways for developing new opioid analgesics with an improved risk-benefit profile.

Identification of 1,3,8-Triazaspiro[4.5]Decane-2,4-Dione Derivatives as a Novel δ Opioid Receptor-Selective Agonist Chemotype

δ opioid receptors (DORs) hold potential as a target for neurologic and psychiatric disorders, yet no DOR agonist has proven efficacious in critical phase II clinical trials. The exact reasons for the failure to produce quality drug candidates for the DOR are unclear. However, it is known that certain DOR agonists can induce seizures and exhibit tachyphylaxis. Several studies have suggested that those adverse effects are more prevalent in delta agonists that share the (+)-4-[(αR)-α-((2S,5R)-4-allyl-2,5-dimethyl-1-piperazinyl)-3-methoxybenzyl]-N,N-diethylbenzamide (SNC80)/4-[(αR*)-α-((2S*,5R*)-4-allyl-2,5-dimethyl-1-piperazinyl)-3-hydroxybenzyl]-N,N-diethylbenzamide chemotype. There is a need to find novel lead candidates for drug development that have improved pharmacological properties to differentiate them from the current failed delta agonists. Our objective in this study was to identify novel DOR agonists. We used a β-arrestin assay to screen a small G-protein coupled receptors (GPCR)-focused chemical library. We identified a novel chemotype of DOR agonists that appears to bind to the orthosteric site based of docking and molecular dynamic simulation. The most potent agonist hit compound is selective for the DOR over a panel of 167 other GPCRs, is slightly biased toward G-protein signaling and has anti-allodynic efficacy in a complete Freund's adjuvant model of inflammatory pain in C57BL/6 male and female mice. The newly discovered chemotype contrasts with molecules like SNC80 that are highly efficacious β-arrestin recruiters and may suggest this novel class of DOR agonists could be expanded on to develop a clinical candidate drug. SIGNIFICANCE STATEMENT: δ opioid receptors are a clinical target for various neurological disorders, including migraine and chronic pain. Many of the clinically tested delta opioid agonists share a single chemotype, which carries risks during drug development. Through a small-scale high-throughput screening assay, this study identified a novel δ opioid receptor agonist chemotype, which may serve as alternative for the current analgesic clinical candidates.

Peptide-derived ligands for the discovery of safer opioid analgesics

Drugs targeting the μ-opioid receptor (MOR) remain the most efficacious analgesics for the treatment of pain, but activation of MOR with current opioid analgesics also produces harmful side effects, notably physical dependence, addiction, and respiratory depression. Opioid peptides have been accepted as promising candidates for the development of safer and more efficacious analgesics. To develop peptide-based opioid analgesics, strategies such as modification of endogenous opioid peptides, development of multifunctional opioid peptides, G protein-biased opioid peptides, and peripherally restricted opioid peptides have been reported. This review seeks to provide an overview of the opioid peptides that produce potent antinociception with much reduced side effects in animal models and highlight the potential advantages of peptides as safer opioid analgesics.

Multitarget μ-Opioid Receptor Agonists─Neuropeptide FF Receptor Antagonists Induce Potent Antinociception with Reduced Adverse Side Effects

The design of bifunctional compounds is a promising approach toward the development of strong analgesics with reduced side effects. We here report the optimization of the previously published lead peptide KGFF09, which contains opioid receptor agonist and neuropeptide FF receptor antagonist pharmacophores and is shown to induce potent antinociception and reduced side effects. We evaluated the novel hybrid peptides for their in vitro activity at MOP, NPFFR1, and NPFFR2 and selected four of them (DP08/14/32/50) for assessment of their acute antinociceptive activity in mice. We further selected DP32 and DP50 and observed that their antinociceptive activity is mostly peripherally mediated; they produced no respiratory depression, no hyperalgesia, significantly less tolerance, and strongly attenuated withdrawal syndrome, as compared to morphine and the recently FDA-approved TRV130. Overall, these data suggest that MOP agonist/NPFF receptor antagonist hybrids might represent an interesting strategy to develop novel analgesics with reduced side effects.

Structure-Activity Relationships of a Novel Cyclic Hexapeptide That Exhibits Multifunctional Opioid Agonism and Produces Potent Antinociceptive Activity

The cyclic peptide c[d-Lys2, Asp5]-DN-9 has recently been identified as a multifunctional opioid/neuropeptide FF receptor agonist, displaying potent analgesic activity with reduced side effects. This study utilized Tyr-c[d-Lys-Gly-Phe-Asp]-d-Pro-NH2 (0), a cyclic hexapeptide derived from the opioid pharmacophore of c[d-Lys2, Asp5]-DN-9, as a chemical template. We designed, synthesized, and characterized 22 analogs of 0 with a single amino acid substitution to investigate its structure-activity relationship. Most of these cyclic hexapeptide analogs exhibited multifunctional activity at μ and δ opioid receptors (MOR and DOR, respectively) and produced antinociceptive effects following subcutaneous administration. The lead compound analog 15 showed potent agonistic activities at the MOR, κ opioid receptor (KOR), and DOR in vitro and produced a strong and long-lasting analgesic effect through peripheral MOR and KOR in the tail-flick test. Further biological evaluation identified that analog 15 did not cause significant side effects such as tolerance, withdrawal, or reward liability.

The opioid receptor: emergence through millennia of pharmaceutical sciences

Throughout history humanity has searched for an optimal approach to the use of opioids that maximizes analgesia while minimizing side effects. This review reflects upon the conceptualization of the opioid receptor and the critical role that the pharmaceutical sciences played in its revelation. Opium-containing formulations have been delivered by various routes of administration for analgesia and other therapeutic indications for millennia. The concept of a distinct site of opium action evolved as practitioners developed innovative delivery methods, such as intravenous administration, to improve therapeutic outcomes. The introduction of morphine and synthetic opioids engendered the prevalent assumption of a common opioid receptor. Through consideration of structure-activity relationships, spatial geometry, and pharmacological differences of known ligands, the idea of multiple opioid receptors emerged. By accessing the high-affinity property of naloxone, the opioid receptor was identified in central and peripheral nervous system tissue. The endogenous opioid neuropeptides were subsequently discovered. Application of mu-, delta-, and kappa- opioid receptor-selective ligands facilitated the pharmacological characterization and distinctions between the three receptors, which were later cloned and sequenced. Opioid receptor signal transduction pathways were described and attributed to specific physiological outcomes. The crystal structures of mu, delta, kappa, and nociceptin/orphanin FQ receptors bound to receptor-selective ligands have been elucidated. Comparison of these structures reveal locations of ligand binding and engagement of signal transduction pathways. Expanding knowledge regarding the structure and actions of the opioid receptor fuels contemporary strategies for driving the activity of opioid receptors toward maximizing therapeutic and minimizing adverse outcomes.

Enhancing Opioid Bioactivity Predictions through Integration of Ligand-Based and Structure-Based Drug Discovery Strategies with Transfer and Deep Learning Techniques

The opioid epidemic has cast a shadow over public health, necessitating immediate action to address its devastating consequences. To effectively combat this crisis, it is crucial to discover better opioid drugs with reduced addiction potential. Artificial intelligence-based and other machine learning tools, particularly deep learning models, have garnered significant attention in recent years for their potential to advance drug discovery. However, utilizing these tools poses challenges, especially when training samples are insufficient to achieve adequate prediction performance. In this study, we investigate the effectiveness of transfer learning using combined ligand-based and structure-based molecular descriptors from the entire opioid receptor (OR) subfamily in building robust deep learning models for enhanced bioactivity prediction of opioid ligands at each individual OR subtype. Our studies hold the potential to greatly advance opioid research by enabling the rapid identification of novel chemical probes with specific bioactivities, which can aid in the study of receptor function and contribute to the future development of improved opioid therapeutics.

Photoinduced C(sp3)-H Functionalization of Glycine Derivatives: Preparation of Unnatural α-Amino Acids and Late-Stage Modification of Peptides

ConspectusPeptides are essential components of living systems and contribute to critical biological processes, such as cell proliferation, immune defense, tumor formation, and differentiation. Therefore, peptides have attracted considerable attention as targets for the development of therapeutic products. The incorporation of unnatural amino acid residues into peptides can considerably impact peptide immunogenicity, toxicity, side effects, water solubility, action duration, and distribution and enhance the peptides' druggability. Typically, the direct modification of natural amino acids is a practical and effective approach for promptly obtaining unnatural amino acids. However, selective functionalization of multiple C(sp³)-H bonds with comparable chemical reactivities in the peptide side chains remains a formidable challenge. Furthermore, chemical modifications aimed at highly reactive (nucleophilic and aromatic) groups on peptide side chains can interfere with the biological activity of peptides.In recent years, the rapid advancement of photoinduced radical reactions has made photoredox radical-radical cross-coupling a practical approach for constructing C(sp³)-C(sp³) bonds under mild conditions. Glycine, a naturally occurring amino acid and the fundamental skeleton of all α-amino acids, provides a basis for the alkylated modification of its own α-C(sp³)-H bond under mild conditions. This Account describes our recent research endeavors for systematically investigating the photocatalytic α-C(sp³)-H alkylation of glycine derivatives via radical-radical coupling between N-aryl glycinate-derived radicals and various alkyl radicals. In 2018, we disclosed the photoinduced Cu-catalyzed decarboxylative α-C(sp³)-H alkylation of glycine derivatives. Subsequently, we developed a catalyst-free method for alkylating glycine derivatives and glycine residues in peptides via electron donor-acceptor (EDA)-complex-promoted single electron transfer. Moreover, we developed a photoinduced method for the radical alkylation of N-aryl glycinate α-C(sp³)-H bonds using unactivated alkyl chlorides (iodides) under photocatalyst-free conditions. Notably, by building on racemic alkylations of glycine derivatives and glycine-residue-containing peptides, we recently stereoselectively alkylated the N-aryl glycinate α-C(sp³)-H bond using a dual-functional Cu catalyst generated in situ for synthesizing a series of unnatural chiral α-amino and C-glycoamino acids.We have developed a series of methods for synthesizing unnatural amino acids through the α-C(sp³)-H alkylation of glycine derivatives using photoredox-promoted radical coupling as a key strategy. These methods are efficient and versatile and can be used for the late-stage modification of peptides in various contexts. Our work builds on the fundamental importance of glycine as the basic scaffold of all α-amino acids and highlights the potential of radical-based chemistry for developing chemical transformations in peptide synthesis. These findings have broad implications for chemical biology and may open doors for discovering peptide drugs and developing therapeutics.

Involvement of the Opioid Peptide Family in Cancer Progression

Peptides mediate cancer progression favoring the mitogenesis, migration, and invasion of tumor cells, promoting metastasis and anti-apoptotic mechanisms, and facilitating angiogenesis/lymphangiogenesis. Tumor cells overexpress peptide receptors, crucial targets for developing specific treatments against cancer cells using peptide receptor antagonists and promoting apoptosis in tumor cells. Opioids exert an antitumoral effect, whereas others promote tumor growth and metastasis. This review updates the findings regarding the involvement of opioid peptides (enkephalins, endorphins, and dynorphins) in cancer development. Anticancer therapeutic strategies targeting the opioid peptidergic system and the main research lines to be developed regarding the topic reviewed are suggested. There is much to investigate about opioid peptides and cancer: basic information is scarce, incomplete, or absent in many tumors. This knowledge is crucial since promising anticancer strategies could be developed alone or in combination therapies with chemotherapy/radiotherapy.

Nitro-benzylideneoxymorphone, a bifunctional mu and delta opioid receptor ligand with high mu opioid receptor efficacy

Introduction: There is a major societal need for analgesics with less tolerance, dependence, and abuse liability. Preclinical rodent studies suggest that bifunctional ligands with both mu (MOPr) and delta (DOPr) opioid peptide receptor activity may produce analgesia with reduced tolerance and other side effects. This study explores the structure-activity relationships (SAR) of our previously reported MOPr/DOPr lead, benzylideneoxymorphone (BOM) with C7-methylene-substituted analogs. Methods: Analogs were synthesized and tested in vitro for opioid receptor binding and efficacy. One compound, nitro-BOM (NBOM, 12) was evaluated for antinociceptive effects in the warm water tail withdrawal assay in C57BL/6 mice. Acute and chronic antinociception was determined, as was toxicologic effects on chronic administration. Molecular modeling experiments were performed using the Site Identification by Ligand Competitive Saturation (SILCS) method. Results: NBOM was found to be a potent MOPr agonist/DOPr partial agonist that produces high-efficacy antinociception. Antinociceptive tolerance was observed, as was weight loss; this toxicity was only observed with NBOM and not with BOM. Modeling supports the hypothesis that the increased MOPr efficacy of NBOM is due to the substituted benzylidene ring occupying a nonpolar region within the MOPr agonist state. Discussion: Though antinociceptive tolerance and non-specific toxicity was observed on repeated administration, NBOM provides an important new tool for understanding MOPr/DOPr pharmacology.

Receptor expression and signaling properties in the brain, and structural ligand motifs that contribute to delta opioid receptor agonist-induced seizures

The δ opioid receptor (δOR) is a therapeutic target for the treatment of various neurological disorders, such as migraines, chronic pain, alcohol use, and mood disorders. Relative to μ opioid receptor agonists, δOR agonists show lower abuse liability and may be potentially safer analgesic alternatives. However, currently no δOR agonists are approved for clinical use. A small number of δOR agonists reached Phase II trials, but ultimately failed to progress due to lack of efficacy. One side effect of δOR agonism that remains poorly understood is the ability of δOR agonists to produce seizures. The lack of a clear mechanism of action is partly driven by the fact that δOR agonists range in their propensity to induce seizure behavior, with multiple δOR agonists reportedly not causing seizures. There is a significant gap in our current understanding of why certain δOR agonists are more likely to induce seizures, and what signal-transduction pathway and/or brain area is engaged to produce these seizures. In this review we provide a comprehensive overview of the current state of knowledge of δOR agonist-mediated seizures. The review was structured to highlight which agonists produce seizures, which brain regions have been implicated and which signaling mediators have been examined in this behavior. Our hope is that this review will spur future studies that are carefully designed and aimed to solve the question why certain δOR agonists are seizurogenic. Obtaining such insight may expedite the development of novel δOR clinical candidates without the risk of inducing seizures. This article is part of the Special Issue on "Opioid-induced changes in addiction and pain circuits".

Reversal of subtype-selectivity and function by the introduction of a para-benzamidyl substituent to N-cyclopropylmethyl nornepenthone

The discovery and development of novel μ-opioid receptor (MOR) antagonists is a significant area to combat Opioid Use Disorder (OUD). In this work, a series of para-substituted N-cyclopropylmethyl-nornepenthone derivatives were designed and synthesized and pharmacologically assayed. Compound 6a was identified as a selective MOR antagonist both in vitro and in vivo. Its molecular basis was elucidated using molecular docking and MD simulations. A subpocket on the extracellular side of the TM2 domain of MOR, in particular the residue Y^2.64, was proposed to be responsible for the reversal of subtype selectivity and functional reversal of this compound.

Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor

The United States is experiencing the most profound and devastating opioid crisis in history, with the number of deaths involving opioids, including prescription and illegal opioids, continuing to climb over the past two decades. This severe public health issue is difficult to combat as opioids remain a crucial treatment for pain, and at the same time, they are also highly addictive. Opioids act on the opioid receptor, which in turn activates its downstream signaling pathway that eventually leads to an analgesic effect. Among the four types of opioid receptors, the µ subtype is primarily responsible for the analgesic cascade. This review describes available 3D structures of the µ opioid receptor in the protein data bank and provides structural insights for the binding of agonists and antagonists to the receptor. Comparative analysis on the atomic details of the binding site in these structures was conducted and distinct binding interactions for agonists, partial agonists, and antagonists were observed. The findings in this article deepen our understanding of the ligand binding activity and shed some light on the development of novel opioid analgesics which may improve the risk benefit balance of existing opioids.

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.

Gluten Exorphins Promote Cell Proliferation through the Activation of Mitogenic and Pro-Survival Pathways

Celiac disease (CD) is a chronic and systemic autoimmune disorder that affects preferentially the small intestine of individuals with a genetic predisposition. CD is promoted by the ingestion of gluten, a storage protein contained in the endosperm of the seeds of wheat, barley, rye, and related cereals. Once in the gastrointestinal (GI) tract, gluten is enzymatically digested with the consequent release of immunomodulatory and cytotoxic peptides, i.e., 33mer and p31-43. In the late 1970s a new group of biologically active peptides, called gluten exorphins (GEs), was discovered and characterized. In particular, these short peptides showed a morphine-like activity and high affinity for the δ-opioid receptor (DOR). The relevance of GEs in the pathogenesis of CD is still unknown. Recently, it has been proposed that GEs could contribute to asymptomatic CD, which is characterized by the absence of symptoms that are typical of this disorder. In the present work, GEs cellular and molecular effects were in vitro investigated in SUP-T1 and Caco-2 cells, also comparing viability effects with human normal primary lymphocytes. As a result, GEs treatments increased tumor cell proliferation by cell cycle and Cyclins activation as well as by induction of mitogenic and pro-survival pathways. Finally, a computational model of GEs interaction with DOR is provided. Altogether, the results might suggest a possible role of GEs in CD pathogenesis and on its associated cancer comorbidities.

Structural Understanding of Peptide-Bound G Protein-Coupled Receptors: Peptide-Target Interactions

The activation of G protein-coupled receptors (GPCRs) is triggered by ligand binding to their orthosteric sites, which induces ligand-specific conformational changes. Agonists and antagonists bound to GPCR orthosteric sites provide detailed information on ligand-binding modes. Among these, peptide ligands play an instrumental role in GPCR pharmacology and have attracted increased attention as therapeutic drugs. The recent breakthrough in GPCR structural biology has resulted in the remarkable availability of peptide-bound GPCR complexes. Despite the several structural similarities shared by these receptors, they exhibit distinct features in terms of peptide recognition and receptor activation. From this perspective, we have summarized the current status of peptide-bound GPCR structural complexes, largely focusing on the interactions between the receptor and its peptide ligand at the orthosteric site. In-depth structural investigations have yielded valuable insights into the molecular mechanisms underlying peptide recognition. This study would contribute to the discovery of GPCR peptide drugs with improved therapeutic effects.

Structures of the entire human opioid receptor family

Opioids are effective analgesics, but their use is beset by serious side effects, including addiction and respiratory depression, which contribute to the ongoing opioid crisis. The human opioid system contains four opioid receptors (μOR, δOR, κOR, and NOPR) and a set of related endogenous opioid peptides (EOPs), which show distinct selectivity toward their respective opioid receptors (ORs). Despite being key to the development of safer analgesics, the mechanisms of molecular recognition and selectivity of EOPs to ORs remain unclear. Here, we systematically characterize the binding of EOPs to ORs and present five structures of EOP-OR-Gi complexes, including β-endorphin- and endomorphin-bound μOR, deltorphin-bound δOR, dynorphin-bound κOR, and nociceptin-bound NOPR. These structures, supported by biochemical results, uncover the specific recognition and selectivity of opioid peptides and the conserved mechanism of opioid receptor activation. These results provide a structural framework to facilitate rational design of safer opioid drugs for pain relief.

A novel strategy for designing the magic shotguns for distantly related target pairs

Due to its promising capacity in improving drug efficacy, polypharmacology has emerged to be a new theme in the drug discovery of complex disease. In the process of novel multi-target drugs (MTDs) discovery, in silico strategies come to be quite essential for the advantage of high throughput and low cost. However, current researchers mostly aim at typical closely related target pairs. Because of the intricate pathogenesis networks of complex diseases, many distantly related targets are found to play crucial role in synergistic treatment. Therefore, an innovational method to develop drugs which could simultaneously target distantly related target pairs is of utmost importance. At the same time, reducing the false discovery rate in the design of MTDs remains to be the daunting technological difficulty. In this research, effective small molecule clustering in the positive dataset, together with a putative negative dataset generation strategy, was adopted in the process of model constructions. Through comprehensive assessment on 10 target pairs with hierarchical similarity-levels, the proposed strategy turned out to reduce the false discovery rate successfully. Constructed model types with much smaller numbers of inhibitor molecules gained considerable yields and showed better false-hit controllability than before. To further evaluate the generalization ability, an in-depth assessment of high-throughput virtual screening on ChEMBL database was conducted. As a result, this novel strategy could hierarchically improve the enrichment factors for each target pair (especially for those distantly related/unrelated target pairs), corresponding to target pair similarity-levels.

Solving an Old Puzzle: Elucidation and Evaluation of the Binding Mode of Salvinorin A at the Kappa Opioid Receptor

The natural product Salvinorin A (SalA) was the first nitrogen-lacking agonist discovered for the opioid receptors and exhibits high selectivity for the kappa opioid receptor (KOR) turning SalA into a promising analgesic to overcome the current opioid crisis. Since SalA's suffers from poor pharmacokinetic properties, particularly the absence of gastrointestinal bioavailability, fast metabolic inactivation, and subsequent short duration of action, the rational design of new tailored analogs with improved clinical usability is highly desired. Despite being known for decades, the binding mode of SalA within the KOR remains elusive as several conflicting binding modes of SalA were proposed hindering the rational design of new analgesics. In this study, we rationally determined the binding mode of SalA to the active state KOR by in silico experiments (docking, molecular dynamics simulations, dynophores) in the context of all available mutagenesis studies and structure-activity relationship (SAR) data. To the best of our knowledge, this is the first comprehensive evaluation of SalA's binding mode since the determination of the active state KOR crystal structure. SalA binds above the morphinan binding site with its furan pointing toward the intracellular core while the C2-acetoxy group is oriented toward the extracellular loop 2 (ECL2). SalA is solely stabilized within the binding pocket by hydrogen bonds (C210ECL2, Y3127.35, Y3137.36) and hydrophobic contacts (V1182.63, I1393.33, I2946.55, I3167.39). With the disruption of this interaction pattern or the establishment of additional interactions within the binding site, we were able to rationalize the experimental data for selected analogs. We surmise the C2-substituent interactions as important for SalA and its analogs to be experimentally active, albeit with moderate frequency within MD simulations of SalA. We further identified the non-conserved residues 2.63, 7.35, and 7.36 responsible for the KOR subtype selectivity of SalA. We are confident that the elucidation of the SalA binding mode will promote the understanding of KOR activation and facilitate the development of novel analgesics that are urgently needed.

Protein Design Strategies for the Structural–Functional Studies of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are an important family of membrane proteins responsible for many physiological functions in human body. High resolution GPCR structures are required to understand their molecular mechanisms and perform rational drug design, as GPCRs play a crucial role in a variety of diseases. That is difficult to obtain for the wild-type proteins because of their low stability. In this review, we discuss how this problem can be solved by using protein design strategies developed to obtain homogeneous stabilized GPCR samples for crystallization and cryoelectron microscopy.

Key Residues in δ Opioid Receptor Allostery Explored by the Elastic Network Model and the Complex Network Model Combined with the Perturbation Method

Opioid receptors, a kind of G protein-coupled receptors (GPCRs), mainly mediate an analgesic response via allosterically transducing the signal of endogenous ligand binding in the extracellular domain to couple to effector proteins in the intracellular domain. The δ opioid receptor (DOP) is associated with emotional control besides pain control, which makes it an attractive therapeutic target. However, its allosteric mechanism and key residues responsible for the structural stability and signal communication are not completely clear. Here we utilize the Gaussian network model (GNM) and amino acid network (AAN) combined with perturbation methods to explore the issues. The constructed fcfGNM_MD, where the force constants are optimized with the inverse covariance estimation based on the correlated fluctuations from the available DOP molecular dynamics (MD) ensemble, shows a better performance than traditional GNM in reproducing residue fluctuations and cross-correlations and in capturing functionally low-frequency modes. Additionally, fcfGNM_MD can consider implicitly the environmental effects to some extent. The lowest mode can well divide DOP segments and identify the two sodium ion (important allosteric regulator) binding coordination shells, and from the fastest modes, the key residues important for structure stabilization are identified. Using fcfGNM_MD combined with a dynamic perturbation-response method, we explore the key residues related to the sodium ion binding. Interestingly, we identify not only the key residues in sodium ion binding shells but also the ones far away from the perturbation sites, which are involved in binding with DOP ligands, suggesting the possible long-range allosteric modulation of sodium binding for the ligand binding to DOP. Furthermore, utilizing the weighted AAN combined with attack perturbations, we identify the key residues for allosteric communication. This work helps strengthen the understanding of the allosteric communication mechanism in δ opioid receptor and can provide valuable information for drug design.

Molecular recognition of morphine and fentanyl by the human μ-opioid receptor

Morphine and fentanyl are among the most used opioid drugs that confer analgesia and unwanted side effects through both G protein and arrestin signaling pathways of μ-opioid receptor (μOR). Here, we report structures of the human μOR-G protein complexes bound to morphine and fentanyl, which uncover key differences in how they bind the receptor. We also report structures of μOR bound to TRV130, PZM21, and SR17018, which reveal preferential interactions of these agonists with TM3 side of the ligand-binding pocket rather than TM6/7 side. In contrast, morphine and fentanyl form dual interactions with both TM3 and TM6/7 regions. Mutations at the TM6/7 interface abolish arrestin recruitment of μOR promoted by morphine and fentanyl. Ligands designed to reduce TM6/7 interactions display preferential G protein signaling. Our results provide crucial insights into fentanyl recognition and signaling of μOR, which may facilitate rational design of next-generation analgesics.

Designer Benzodiazepines' Activity on Opioid Receptors: A Docking Study

BACKGROUND

Previous studies have reported that benzodiazepines (BZDs) seem to enhance euphoric and reinforcing properties of opioids in opioid users so that a direct effect on opioid receptors has been postulated, together with a possible synergistic induction of severe side effects due to co use of BDZs and opioids. This is particularly worrisome given the appearance on the market of designer benzodiazepines (DBZDs), whose activity/toxicity profiles are scarcely known.

OBJECTIVES

This study aimed to evaluate, through computational studies, the binding affinity (or lack thereof) of 101 DBZDs identified online on the kappa, mu, and delta opioid receptors (K, M, DOR); and to assess whether their mechanism of action could include activation of the latter.

METHODS

MOE® was used for the computational studies. Pharmacophore mapping based on strong opioids agonist binders' 3D chemical features was used to filter the DBZDs. Resultant DBZDs were docked into the crystallised 3D active conformation of KOR (PDB6B73), DOR (PDB6PT3) and MOR (PDB5C1M). Co-crystallised ligands and four strong agonists were used as reference compounds. A score (S, Kcal/mol) representative of the predicted binding affinity, and a description of ligand interactions were obtained from MOE®.

RESULTS

The docking results, filtered for S < -8.0 and the interaction with the Asp residue, identified five DBZDs as putative binders of the three ORs : ciclotizolam, fluloprazolam, JQ1, Ro 48-6791, and Ro 48-8684.

CONCLUSION

It may be inferred that at least some DBZDs may have the potential to activate opioid receptors. This could mediate/increase their anxiolytic, analgesic, and addiction potentials, as well as worsen the side effects associated with opioid co-use.

Immunomodulatory Role of Neuropeptides in the Cornea

The transparency of the cornea along with its dense sensory innervation and resident leukocyte populations make it an ideal tissue to study interactions between the nervous and immune systems. The cornea is the most densely innervated tissue of the body and possesses both immune and vascular privilege, in part due to its unique repertoire of resident immune cells. Corneal nerves produce various neuropeptides that have a wide range of functions on immune cells. As research in this area expands, further insights are made into the role of neuropeptides and their immunomodulatory functions in the healthy and diseased cornea. Much remains to be known regarding the details of neuropeptide signaling and how it contributes to pathophysiology, which is likely due to complex interactions among neuropeptides, receptor isoform-specific signaling events, and the inflammatory microenvironment in disease. However, progress in this area has led to an increase in studies that have begun modulating neuropeptide activity for the treatment of corneal diseases with promising results, necessitating the need for a comprehensive review of the literature. This review focuses on the role of neuropeptides in maintaining the homeostasis of the ocular surface, alterations in disease settings, and the possible therapeutic potential of targeting these systems.

Exploring Conformational Preferences of Leu-enkephalin Using the Conformational Search and Double-Hybrid DFT Energy Calculations

The conformational preferences of Leu-enkephalin (Leu-Enk) were explored by the conformational search and density functional theory (DFT) calculations. By a combination of low-energy conformers of each residue, the initial structures of the neutral Leu-Enk were generated and optimized using the ECEPP3 force field in the gas phase. These structures were reoptimized at the HF/3-21G(d) and M06-2X levels of theory with 6-31G(d) and 6-31+G(d) basis functions. We finally located the 139 structures with the relative energy <10 kcal mol-1 in the gas phase, from which the structures of the corresponding zwitterionic Leu-Enk were generated and reoptimized at the M06-2X/6-31+G(d) level of theory using the implicit solvation model based on density (SMD) in water. The conformational preferences of Leu-Enk were analyzed using Gibbs free energies corrected by single-point energies calculated at the double-hybrid DSD-PBEP86-D3BJ/def2-TZVP level of theory in the gas phase and in water. The neutral Leu-Enk dominantly adopted a folded structure in the gas phase stabilized by three H-bonds with a βII'-bend-like motif at the Gly3-Phe4 sequence and a close contact between the side chains of Phe4 and Leu5. The zwitterionic Leu-Enk exhibited a folded structure in water stabilized by three H-bonds with double β-bends such as a βII' bend at the Gly2-Gly3 sequence and a βI bend at the Gly3-Phe4 sequence. The calculated ensemble-averaged distance between CGly2 α and CLeu5 α of the zwitterionic Leu-Enk in water is consistent with the value estimated from the simulated annealing using the distance constraints derived from nuclear Overhauser effect spectroscopy (NOESY) spectra in water. Interestingly, the preferred conformations of the neutral and zwitterionic Leu-Enk are new folded structures not predicted by earlier computational studies. According to the refined model of the zwitterionic Leu-Enk bound to δ-opioid receptor (δOR), there were favorable interactions of the terminal charged groups of Leu-Enk with the side chains of charged residues of δOR as well as a favorable CAryl···H interaction of the Phe4 residue of Leu-Enk with Trp284 of δOR. Hence, these favorable interactions would induce the folded structure of the zwitterionic Leu-Enk with double β-bends isolated in water into the "bioactive conformation" like an extended structure when binding to δOR.

To probe the activation mechanism of the Delta opioid receptor by an agonist ADL5859 started from inactive conformation using molecular dynamic simulations

The δ-opioid receptor (DOR) is a critical pharmaceutical target for pain management. Although the high-resolution crystal structures of the DOR with both agonist and antagonist have recently been solved, the activation mechanism remains to be elusive. In this study, a DOR agonist ADL5859 was docked to the inactive DOR and multiple microsecond molecular dynamic (MD) simulations were conducted to probe the activation mechanism. While the receptor with the crystal ligand (i.e. antagonist naltrindole) maintained the inactive conformation in all three independent simulations, the receptor with ADL5859 was adopting toward the active conformation in three out of six independent simulations. Major conformational differences were located on transmembrane (TM) 5 and 6, as well as intracellular loop 3. Compared to naltrindole, ADL5859 exhibited high conformational flexibility and strong interaction with the transmission switch. The putative key residues (W274, D95, V267, L139, V263, M142, T260, R146, R258 and others) involving in the activation pathway were identified through the conventional molecular switch analysis and a pairwise distance analysis, which provides a short list for experimental mutagenesis study. These insights will facilitate further development of therapeutic agents targeting the DOR.Communicated by Ramaswamy H. Sarma.

Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors

The delta opioid receptor is a Gi-protein-coupled receptor (GPCR) with a broad expression pattern both in the central nervous system and the body. The receptor has been investigated as a potential target for a multitude of significant diseases including migraine, alcohol use disorder, ischemia, and neurodegenerative diseases. Despite multiple attempts, delta opioid receptor-selective molecules have not been translated into the clinic. Yet, the therapeutic promise of the delta opioid receptor remains and thus there is a need to identify novel delta opioid receptor ligands to be optimized and selected for clinical trials. Here, we highlight recent developments involving the delta opioid receptor, the closely related mu and kappa opioid receptors, and in the broader area of the GPCR drug discovery research. We focus on the validity and utility of the available delta opioid receptor structures. We also discuss the increased ability to perform ultra-large-scale docking studies on GPCRs, the rise in high-resolution cryo-EM structures, and the increased prevalence of machine learning and artificial intelligence in drug discovery. Overall, we pose that there are multiple opportunities to enable in silico drug discovery at the delta opioid receptor to identify novel delta opioid modulators potentially with unique pharmacological properties, such as biased signaling.

Antidepressant-like effect of tofisopam in mice: A behavioural, molecular docking and MD simulation study

BACKGROUND

Depression is a disease that affects millions of people worldwide, and the discovery and development of effective and safe antidepressant drugs is one of the important topics of psychopharmacology.

OBJECTIVES

In this study, it was aimed to investigate the antidepressant-like activity potential of tofisopam, an anxiolytic drug with 2,3-benzodiazepine structure, and to elucidate the pharmacological mechanisms mediating this effect.

METHODS

The antidepressant-like activity of tofisopam was investigated using tail suspension and modified forced swimming tests. Possible interactions of tofisopam with µ- and δ-opioid receptor subtypes were clarified by pharmacological antagonism, molecular docking and molecular dynamics simulation studies.

RESULTS

Tofisopam (50 and 100 mg/kg) significantly shortened the immobility time of mice in both the tail suspension and the modified forced swimming tests. The drug, at the same doses, prolonged the duration of swimming and climbing behaviours measured in modified forced swimming tests. A dosage of 25 mg/kg was ineffective. Mechanistic studies showed that the pretreatment with p-chlorophenylalanine methyl ester (serotonin synthesis inhibitor; 4 consecutive days, 100 mg/kg), α-methyl-para-tyrosine methyl ester (catecholamine synthesis inhibitor; 100 mg/kg), naloxonazine (selective µ-opioid receptor blocker, 7 mg/kg) and naltrindole (a selective δ-opioid receptor blocker, 0.99 mg/kg) abolished the anti-immobility effect induced by the 50 mg/kg dose of tofisopam in the tail suspension tests. Our in silico studies supported the behavioural findings that the antidepressant-like effect of tofisopam is mediated by μ- and δ-opioid receptors.

CONCLUSION

This study is the first to show that tofisopam has antidepressant-like activity mediated by the serotonergic, catecholaminergic and opioidergic systems.

In Vitro, In Vivo and In Silico Characterization of a Novel Kappa-Opioid Receptor Antagonist

Kappa-opioid receptor (KOR) antagonists are promising innovative therapeutics for the treatment of the central nervous system (CNS) disorders. The new scaffold opioid ligand, Compound A, was originally found as a mu-opioid receptor (MOR) antagonist but its binding/selectivity and activation profile at the KOR and delta-opioid receptor (DOR) remain elusive. In this study, we present an in vitro, in vivo and in silico characterization of Compound A by revealing this ligand as a KOR antagonist in vitro and in vivo. In the radioligand competitive binding assay, Compound A bound at the human KOR, albeit with moderate affinity, but with increased affinity than to the human MOR and without specific binding at the human DOR, thus displaying a preferential KOR selectivity profile. Following subcutaneous administration in mice, Compound A effectively reverse the antinociceptive effects of the prototypical KOR agonist, U50,488. In silico investigations were carried out to assess the structural determinants responsible for opioid receptor subtype selectivity of Compound A. Molecular docking, molecular dynamics simulations and dynamic pharmacophore (dynophore) generation revealed differences in the stabilization of the chlorophenyl moiety of Compound A within the opioid receptor binding pockets, rationalizing the experimentally determined binding affinity values. This new chemotype bears the potential for favorable ADMET properties and holds promise for chemical optimization toward the development of potential therapeutics.

Investigation of Tumor Cells and Receptor-Ligand Simulation Models for the Development of PET Imaging Probes Targeting PSMA and GRPR and a Possible Crosstalk between the Two Receptors

Prostate-specific membrane antigen (PSMA) and gastrin-releasing peptide receptor (GRPR) have both been used in nuclear medicine as targets for molecular imaging and therapy of prostate (PCa) and breast cancer (BCa). Three bioconjugate probes, the PSMA specific: [⁶⁸Ga]Ga-1, ((HBED-CC)-Ahx-Lys-NH-CO-NH Glu or PSMA-11), the GRPR specific: [⁶⁸Ga]Ga-2, ((HBED-CC)-4-amino-1-carboxymethyl piperidine-[D-Phe⁶, Sta¹³]BN(6-14), a bombesin (BN) analogue), and 3 (the BN analogue: 4-amino-1-carboxymethyl piperidine-[(R)-Phe⁶, Sta¹³]BN(6-14) connected with the fluorescent dye, BDP-FL), were synthesized and tested in vitro with PCa and BCa cell lines, more specifically, with PCa cells, PC-3 and LNCaP, with BCa cells, T47D, MDA-MB-231, and with the in-house created PSMA-overexpressing PC-3^(PSMA), T47D^(PSMA), and MDA-MB-231^(PSMA). In addition, biomolecular simulations were conducted on the association of 1 and 2 with PSMA and GRPR. The PSMA overexpression resulted in an increase of cell-bound radioligand [⁶⁸Ga]Ga-1 (PSMA) for PCa and BCa cells and also of [⁶⁸Ga]Ga-2 (GRPR), especially in those cell lines already expressing GRPR. The results were confirmed by fluorescence-activated cell sorting with a PE-labeled PSMA-specific antibody and the fluorescence tracer 3. The docking calculations and molecular dynamics simulations showed how 1 enters the PSMA funnel region and how pharmacophore Glu-urea-Lys interacts with the arginine patch, the S1', and S1 subpockets by forming hydrogen and van der Waals bonds. The chelating moiety of 1, that is, HBED-CC, forms additional stabilizing hydrogen bonding and van der Waals interactions in the arene-binding site. Ligand 2 is diving into the GRPR transmembrane (TM) helical cavity, thereby forming hydrogen bonds through its amidated end, water-mediated hydrogen bonds, and π-π interactions. Our results provide valuable information regarding the molecular mechanisms involved in the interactions of 1 and 2 with PSMA and GRPR, which might be useful for the diagnostic imaging and therapy of PCa and BCa.

Activation mechanism of the μ-opioid receptor by an allosteric modulator

SignificanceThe allosteric modulators, which bind to nonorthosteric sites to enhance the signaling activities of G-protein-coupled receptors (GPCRs), are new candidates for GPCR-targeting drugs. Our solution NMR analyses of the μ-opioid receptor (MOR) revealed that the MOR activity was determined by a conformational equilibrium between three conformations. Interestingly, an allosteric modulator shifted the equilibrium toward a conformation with the highest activity to a level that cannot be reached by orthosteric ligands alone, leading to the increased activity of MOR. Our NMR analyses also identified the binding site of the allosteric modulator, including the residues contributing to the regulation of the equilibrium. These findings provide insights into the rational developments of novel allosteric modulators.

Computational Methods for Understanding the Selectivity and Signal Transduction Mechanism of Aminomethyl Tetrahydronaphthalene to Opioid Receptors

Opioid receptors are members of the group of G protein-couple receptors, which have been proven to be effective targets for treating severe pain. The interactions between the opioid receptors and corresponding ligands and the receptor’s activation by different agonists have been among the most important fields in opioid research. In this study, with compound M1, an active metabolite of tramadol, as the clue compound, several aminomethyl tetrahydronaphthalenes were designed, synthesized and assayed upon opioid receptors. With the resultant compounds FW-AII-OH-1 (Ki = 141.2 nM for the κ opioid receptor), FW-AII-OH-2 (Ki = 4.64 nM for the δ opioid receptor), FW-DI-OH-2 (Ki = 8.65 nM for the δ opioid receptor) and FW-DIII-OH-2 (Ki = 228.45 nM for the δ opioid receptor) as probe molecules, the structural determinants responsible for the subtype selectivity and activation mechanisms were further investigated by molecular modeling and molecular dynamics simulations. It was shown that Y^7.43 was a key residue in determining the selectivity of the three opioid receptors, and W^6.58 was essential for the selectivity of the δ opioid receptor. A detailed stepwise discovered agonist-induced signal transduction mechanism of three opioid receptors by aminomethyl tetrahydronaphthalene compounds was proposed: the 3–7 lock between TM3 and TM7, the DRG lock between TM3 and TM6 and rearrangement of I^3.40, P^5.50 and F^6.44, which resulted in the cooperative movement in 7 TMs. Then, the structural relaxation left room for the binding of the G protein at the intracellular site, and finally the opioid receptors were activated.

Universal platform for the generation of thermostabilized GPCRs that crystallize in LCP

Structural studies of G-protein-coupled receptors (GPCRs) are often limited by difficulties in obtaining well-diffracting crystals suitable for high-resolution structure determination. During the past decade, crystallization in lipidic cubic phase (LCP) has become the most successful and widely used technique for obtaining such crystals. Despite often intense efforts, many GPCRs remain refractory to crystallization, even if receptors can be purified in sufficient amounts. To address this issue, we have developed a highly efficient screening and stabilization strategy for GPCRs, based on a fluorescence thermal stability assay readout, which seems to correlate particularly well with those GPCR constructs that remain native during incorporation into the LCP. Detailed protocols are provided for rapid and cost-efficient mutant and construct generation using sequence- and ligation-independent cloning, high-throughput magnetic bead-based protein purification from small-scale expressions in mammalian cells, the screening and optimal combination of mutations for increased receptor thermostability and the rapid identification of suitable chimeric fusion protein constructs for successful crystallization in LCP. We exemplify the method on three receptors from two different classes: the neurokinin 1 receptor, the oxytocin receptor and the parathyroid hormone 1 receptor.