Residues W320 and Y328 within the binding site of the μ-opioid receptor influence opiate ligand bias

Identification and functional analysis of six melanocortin-4-receptor-like (MC4R-like) mutations in goldfish (Carassius auratus)

Melanocortin receptor-4 (MC4R) belongs to the G protein-coupled receptor family, characterized by a classical structure of seven transmembrane domains (7TMD). They play an important role in food intake and weight regulation. In the present study, we identified melanocortin-4-receptor-like (caMC4RL) mutants of goldfish from the Qian River in the Qin Ling region and characterized their functional properties, including the constitutive activities of the mutants, ligand-induced cAMP and ERK1/2 accumulation, and AMPK activation. The results show that six caMC4RL mutants were identified in goldfish from the Qian River in the Qin Ling region, and are located in the conserved position of the Cyprinidae MC4Rs. The mutations (E57K, P296S, and R302T/K) result in the loss of Gs signaling function. The mutations (P296 and R302T/K) exhibited biased signaling in response to ACTH stimulation in the MAPK/ERK pathway. In addition, the E57K mutant may play a role in weight regulation and could serve as molecular markers for molecular breeding. These data will provide fundamental information for functional studies of teleost GPCR mutants and MC4R isoforms.

Understanding and Predicting Ligand Efficacy in the μ-Opioid Receptor through Quantitative Dynamical Analysis of Complex Structures

The μ-opioid receptor (MOR) is a G-protein coupled receptor involved in nociception and the primary target of opioid drugs. Understanding the relationships among the ligand structure, receptor dynamics, and efficacy in activating MOR is crucial for drug discovery and development. Here, we use coarse-grained normal-mode analysis to predict ligand-induced changes in receptor dynamics with the Quantitative Dynamics Activity Relationship (QDAR) DynaSig-ML methodology, training a LASSO regression model on the entropic signatures (ESs) computed from ligand-receptor complexes. We train and validate the methodology using a data set of 179 MOR ligands with experimentally measured efficacies split into strictly chemically different cross-validation sets. By analyzing the coefficients of the ES LASSO model, we identified key residues involved in MOR activation, several of which have mutational data supporting their role in MOR activation. Additionally, we explored a contact-only LASSO model based on ligand-protein interactions. While the model showed predictive power, it failed at predicting efficacy for ligands with low structural similarity to the training set, emphasizing the importance of receptor dynamics for predicting ligand-induced receptor activation. Moreover, the low computational cost of our approach, at 3 CPU s per ligand-receptor complex, opens the door to its application in large-scale virtual screening contexts. Our work contributes to a better understanding of dynamics-function relationships in the μ-opioid receptor and provides a framework for predicting ligand efficacy based on ligand-induced changes in receptor dynamics.

Signaling Modulation Mediated by Ligand Water Interactions with the Sodium Site at μOR

The mu opioid receptor (μOR) is a target for clinically used analgesics. However, adverse effects, such as respiratory depression and physical dependence, necessitate the development of alternative treatments. Recently we reported a novel strategy to design functionally selective opioids by targeting the sodium binding allosteric site in μOR with a supraspinally active analgesic named C6guano. Presently, to improve systemic activity of this ligand, we used structure-based design, identifying a new ligand named RO76 where the flexible alkyl linker and polar guanidine guano group is swapped with a benzyl alcohol, and the sodium site is targeted indirectly through waters. A cryoEM structure of RO76 bound to the μOR-Gi complex confirmed that RO76 interacts with the sodium site residues through a water molecule, unlike C6guano which engages the sodium site directly. Signaling assays coupled with APEX based proximity labeling show binding in the sodium pocket modulates receptor efficacy and trafficking. In mice, RO76 was systemically active in tail withdrawal assays and showed reduced liabilities compared to those of morphine. In summary, we show that targeting water molecules in the sodium binding pocket may be an avenue to modulate signaling properties of opioids, and which may potentially be extended to other G-protein coupled receptors where this site is conserved.

Investigating selectivity and bias for G protein subtypes and β-arrestins by synthetic cannabinoid receptor agonists at the cannabinoid CB1 receptor

The cannabinoid CB1 receptor (CB1) is a G protein-coupled receptor (GPCR) with widespread expression in the central nervous system. This canonically G⍺i/o-coupled receptor mediates the effects of Δ9-tetrahydrocannabinol (THC) and synthetic cannabinoid receptor agonists (SCRAs). Recreational use of SCRAs is associated with serious adverse health effects, making pharmacological research into these compounds a priority. Several studies have hypothesised that signalling bias may explain the different toxicological profiles between SCRAs and THC. Previous studies have focused on bias between G protein activation measured by cyclic adenosine monophosphate (cAMP) inhibition and β-arrestin translocation. In contrast, the current study characterises bias between G⍺ subtypes of the G⍺i/o family and β-arrestins; this method facilitates a more accurate assessment of ligand bias by assessing signals that have not undergone major amplification. We have characterised G protein dissociation and translocation of β-arrestin 1 and 2 using real-time BRET reporters. The responses produced by each SCRA across the G protein subtypes tested were consistent with the responses produced by the reference ligand AMB-FUBINACA. Ligand bias was probed by applying the operational analysis to determine biases within the G⍺i/o family, and between G protein subtypes and β-arrestins. Overall, these results confirm SCRAs to be balanced, high-efficacy ligands compared to the low efficacy ligand THC, with only one SCRA, 4CN-MPP-BUT7IACA, demonstrating statistically significant bias in one pathway comparison (towards β-arrestin 1 when compared with G⍺oA/oB). This suggests that the adverse effects caused by SCRAs are due to high potency and efficacy at CB1, rather than biased agonism.

Morphinan Evolution: The Impact of Advances in Biochemistry and Molecular Biology

Morphinan-based opioids, derived from natural alkaloids like morphine, codeine and thebaine, have long been pivotal in managing severe pain. However, their clinical utility is marred by significant side effects and high addiction potential. This review traces the evolution of the morphinan scaffold in light of advancements in biochemistry and molecular biology, which have expanded our understanding of opioid receptor pharmacology. We explore the development of semi-synthetic and synthetic morphinans, their receptor selectivity and the emergence of biased agonism as a strategy to dissociate analgesic properties from undesirable effects. By examining the molecular intricacies of opioid receptors and their signaling pathways, we highlight how receptor-type selectivity and signaling bias have informed the design of novel analgesics. This synthesis of historical and contemporary perspectives provides an overview of the morphinan landscape, underscoring the ongoing efforts to mitigate the problems facing opioids through smarter drug design. We also highlight that most morphinan derivatives show a preference for the G protein pathway, although detailed experimental comparisons are still necessary. This fact underscores the utility of the morphinan skeleton in future opioid drug discovery.

Quantitative receptor model for responses that are left- or right-shifted versus occupancy (are more or less concentration sensitive): the SABRE approach

Simple one-to three-parameter models routinely used to fit typical dose-response curves and calculate EC50 values using the Hill or Clark equation cannot provide the full picture connecting measured response to receptor occupancy, which can be quite complex due to the interplay between partial agonism and (pathway-dependent) signal amplification. The recently introduced SABRE quantitative receptor model is the first one that explicitly includes a parameter for signal amplification (γ) in addition to those for binding affinity (K d), receptor-activation efficacy (ε), constitutive activity (ε R0), and steepness of response (Hill slope, n). It can provide a unified framework to fit complex cases, where fractional response and occupancy do not match, as well as simple ones, where parameters constrained to specific values can be used (e.g., ε R0 = 0, γ = 1, or n = 1). Here, it is shown for the first time that SABRE can fit not only typical cases where response curves are left-shifted compared to occupancy (κ = K d/EC50 > 1) due to signal amplification (γ > 1), but also less common ones where they are right-shifted (i.e., less concentration-sensitive; κ = K d/EC50 < 1) by modeling them as apparent signal attenuation/loss (γ < 1). Illustrations are provided with μ-opioid receptor (MOPr) data from three different experiments with one left- and one right-shifted response (G protein activation and β-arrestin2 recruitment, respectively; EC50,Gprt < K d < EC50,βArr). For such cases of diverging pathways with differently shifted responses, partial agonists can cause very weak responses in the less concentration-sensitive pathway without having to be biased ligands due to the combination of low ligand efficacy and signal attenuation/loss-an illustration with SABRE-fitted oliceridine data is included.

IUPHAR themed review: Opioid efficacy, bias, and selectivity

Drugs acting at the opioid receptor family are clinically used to treat chronic and acute pain, though they represent the second line of treatment behind GABA analogs, antidepressants and SSRI's. Within the opioid family mu and kappa opioid receptor are commonly targeted. However, activation of the mu opioid receptor has side effects of constipation, tolerance, dependence, euphoria, and respiratory depression; activation of the kappa opioid receptor leads to dysphoria and sedation. The side effects of mu opioid receptor activation have led to mu receptor drugs being widely abused with great overdose risk. For these reasons, newer safer opioid analgesics are in high demand. For many years a focus within the opioid field was finding drugs that activated the G protein pathway at mu opioid receptor, without activating the β-arrestin pathway, known as biased agonism. Recent advances have shown that this may not be the way forward to develop safer analgesics at mu opioid receptor, though there is still some promise at the kappa opioid receptor. Here we discuss recent novel approaches to develop safer opioid drugs including efficacy vs bias and fine-tuning receptor activation by targeting sub-pockets in the orthosteric site, we explore recent works on the structural basis of bias, and we put forward the suggestion that Gα subtype selectivity may be an exciting new area of interest.

All-Atom Molecular Dynamics Simulations Indicated the Involvement of a Conserved Polar Signaling Channel in the Activation Mechanism of the Type I Cannabinoid Receptor

The type I cannabinoid G protein-coupled receptor (CB1, GPCR) is an intensely investigated pharmacological target, owing to its involvement in numerous physiological functions as well as pathological processes such as cancers, neurodegenerative diseases, metabolic disorders and neuropathic pain. In order to develop modern medications that exert their effects through binding to the CB1 receptor, it is essential to understand the structural mechanism of activation of this protein. The pool of atomic resolution experimental structures of GPCRs has been expanding rapidly in the past decade, providing invaluable information about the function of these receptors. According to the current state of the art, the activity of GPCRs involves structurally distinct, dynamically interconverting functional states and the activation is controlled by a cascade of interconnecting conformational switches in the transmembrane domain. A current challenge is to uncover how different functional states are activated and what specific ligand properties are responsible for the selectivity towards those different functional states. Our recent studies of the μ-opioid and β₂-adrenergic receptors (MOP and β₂AR, respectively) revealed that the orthosteric binding pockets and the intracellular surfaces of these receptors are connected through a channel of highly conserved polar amino acids whose dynamic motions are in high correlation in the agonist- and G protein-bound active states. This and independent literature data led us to hypothesize that, in addition to consecutive conformational transitions, a shift of macroscopic polarization takes place in the transmembrane domain, which is furnished by the rearrangement of polar species through their concerted movements. Here, we examined the CB1 receptor signaling complexes utilizing microsecond scale, all-atom molecular dynamics (MD) simulations in order to see if our previous assumptions could be applied to the CB1 receptor too. Apart from the identification of the previously proposed general features of the activation mechanism, several specific properties of the CB1 have been indicated that could possibly be associated with the signaling profile of this receptor.

Biased Activation Mechanism Induced by GPCR Heterodimerization: Observations from μOR/δOR Dimers

GPCRs regulate multiple intracellular signaling cascades. Biasedly activating one signaling pathway over the others provides additional clinical utility to optimize GPCR-based therapies. GPCR heterodimers possess different functions from their monomeric states, including their selectivity to different transducers. However, the biased signaling mechanism induced by the heterodimerization remains unclear. Motivated by the issue, we select an important GPCR heterodimer (μOR/δOR heterodimer) as a case and use microsecond Gaussian accelerated molecular dynamics simulation coupled with potential of mean force and protein structure network (PSN) to probe mechanisms regarding the heterodimerization-induced constitutive β-arrestin activity and efficacy change of the agonist DAMGO. The results show that only the lowest energy state of the μOR/δOR heterodimer, which adopts a slightly outward shift of TM6 and an ICL2 conformation close to the receptor core, can selectively accommodate β-arrestins. PSN further reveals important roles of H8, ICL1, and ICL2 in regulating the constitutive β-arrestin-biased activity for the apo μOR/δOR heterodimer. In addition, the heterodimerization can allosterically alter the binding mode of DAMGO mainly by means of W7.35. Consequently, DAMGO transmits the structural signal mainly through TM6 and TM7 in the dimer, rather than TM3 similar to the μOR monomer, thus changing the efficacy of DAMGO from a balanced agonist to the β-arrestin-biased one. On the other side, the binding of DAMGO to the heterodimer can stabilize μOR/δOR heterodimers through a stronger interaction of TM1/TM1 and H8/H8, accordingly enhancing the interaction of μOR with δOR and the binding affinity of the dimer to the β-arrestin. The agonist DAMGO does not change main compositions of the regulation network from the dimer interface to the transducer binding pocket of the μOR protomer, but induces an increase in the structural communication of the network, which should contribute to the enhanced β-arrestin coupling. Our observations, for the first time, reveal the molecular mechanism of the biased signaling induced by the heterodimerization for GPCRs, which should be beneficial to more comprehensively understand the GPCR bias signaling.

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.

Tyrosine 7.43 is important for mu-opioid receptor downstream signaling pathways activated by fentanyl

G protein–coupled receptors can signal through both G proteins and ß-arrestin2. For the µ-opioid receptor (MOR), early experimental evidence from a single study suggested that G protein signaling mediates analgesia and sedation, whereas ß-arrestin signaling mediates respiratory depression and constipation. Then, receptor mutations were used to clarify which residues interact with ligands to selectively regulate signals in a ligand-specific manner. However, there is no systematic study on how to determine these residues and clarify the molecular mechanism of their influence on signal pathways. We have therefore used molecular docking to predict the amino acid sites that affect the binding of ligands and MOR. Then, the corresponding sites were mutated to determine the effect of the structural determinant of MOR on G_i/o protein and ß-arrestin pathways. The pharmacological and animal behavioral experiments in combination with molecular dynamics simulations were used to elucidate the molecular mechanism of key residues governing the signaling. Without affecting ligand binding to MOR, MOR^Y7.43A attenuated the activation of both G_i/o protein and ß-arrestin signaling pathways stimulated by fentanyl, whereas it did not change these two pathways stimulated by morphine. Likewise, the activation peak time of extracellular regulated protein kinases was significantly prolonged at MOR^Y7.43A compared with that at MOR^wildtype stimulated by fentanyl, but there was no difference stimulated by morphine. In addition, MOR^Y7.43A significantly enhanced analgesia by fentanyl but not by morphine in the mice behavioral experiment. Furthermore, the molecular dynamics simulations showed that H6 moves toward the cellular membrane. H6 of the fentanyl–Y7.43A system moved outward more than that in the morphine–Y7.43A system. Y7.43 mutation disrupted hydrophobic interactions between W6.48 and Y7.43 in the fentanyl–Y7.43A system but not in the morphine–Y7.43A system. Our results have disclosed novel mechanisms of Y7.43 mutation affecting MOR signaling pathways. Y7.43 mutation reduced the activation of the G_i/o protein pathway and blocked the ß-arrestin2 recruitment, increased the H6 outward movement of MOR, and disrupted hydrophobic interactions. This may be responsible for the enhanced fentanyl analgesia. These findings are conducive to designing new drugs from the perspective of ligand and receptor binding, and Y7.43 is also expected to be a key site to structure optimization of synthesized compounds.

Probing Allosteric Regulation Mechanism of W7.35 on Agonist-Induced Activity for μOR by Mutation Simulation

The residue located at 15 positions before the most conserved residue in TM7 (7.35 of Ballesteros-Weinstein number) plays important roles in ligand binding and the receptor activity for class A GPCRs. Nevertheless, its regulation mechanism has not been clearly clarified in experiments, and some controversies also exist for its impact on μ-opioid receptors (μOR) bound by agonists. Thus, we chose the μ-opioid receptor (μOR) of class A GPCRs as a representative and utilized a microsecond accelerated molecular dynamics simulation (aMD) coupled with a protein structure network (PSN) to explore the effect of W318^7.35 on its functional activity induced by the agonist endomorphin2 mainly by a comparison of the wild system and its W7.35A mutant. When endomorphin2 binds to the wild-type μOR, TM6 in μOR moves outward to form an open intracellular conformation that is beneficial to accommodating the β-arrestin transducer, rather than the G-protein transducer due to the clash with the α5 helix of G-protein, thus acting as a β-arrestin biased agonist. However, the W318A mutation induces the intracellular part of μOR to form a closed state, which disfavors coupling with either G-protein or β-arrestin. The allosteric pathway analysis further reveals that the binding of endomorphin2 to the wild-type μOR transmits more activation signals to the β-arrestin binding site while the W318A mutation induces more structural signals to transmit to common binding residues of the G protein and β-arrestin. More interestingly, the residue at the 7.35 position regulates the shortest allosteric pathway in indirect ways by influencing the interactions between other ligand-binding residues and endomorphin2. W293^6.48 and F289^6.44 are important for regulating the different activities of μOR induced either by the agonist or by the mutation. Y336^7.53, F343^8.50, and D340^8.47 play crucial roles in activating the β-arrestin biased signal induced by the agonist endomorphin2, while L158^3.43 and V286^6.41 devote important contributions to the change in the activity of endomorphin2 from the β-arrestin biased agonist to the antagonist upon the W318A mutation.

Encoding mu-opioid receptor biased agonism with interaction fingerprints

Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein-ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling.

Discovery, Structure-Activity Relationship, and Mechanistic Studies of 1-((3R,4S)-3-((Dimethylamino)methyl)-4-hydroxy-4-(3-methoxyphenyl)piperidin-1-yl)-2-(2,4,5-trifluorophenyl)ethan-1-one as a Novel Potent Analgesic

Management of moderate to severe pain relies heavily on opioid analgesics such as morphine, oxycodone, and fentanyl in clinics. However, their prolonged use was associated with undesirable side effects. Many new strategies to reduce side effects have been proposed, but not without disadvantages. Using a hot plate model as a phenotypic screening method, our studies identified (3R,4S)-9d with a new scaffold as a potent analgesic with ED₅₀ values of 0.54 mg/kg and 0.021 mg/kg in hot plate and antiwrithing models, respectively. Mechanistic studies showed that it elicited its analgesic effect via the active metabolite (3R,4S)-10a. The mechanism of (3R,4S)-10a-induced activation of the μ opioid receptor (MOR) was proposed by means of molecular dynamics (MD) simulation.

Correlated Motions of Conserved Polar Motifs Lay out a Plausible Mechanism of G Protein-Coupled Receptor Activation

Recent advancements in the field of experimental structural biology have provided high-resolution structures of active and inactive state G protein-coupled receptors (GPCRs), a highly important pharmaceutical target family, but the process of transition between these states is poorly understood. According to the current theory, GPCRs exist in structurally distinct, dynamically interconverting functional states of which populations are shifted upon binding of ligands and intracellular signaling proteins. However, explanation of the activation mechanism, on an entirely structural basis, gets complicated when multiple activation pathways and active receptor states are considered. Our unbiased, atomistic molecular dynamics simulations of the μ opioid receptor (MOP) revealed that transmission of external stimulus to the intracellular surface of the receptor is accompanied by subtle, concerted movements of highly conserved polar amino acid side chains along the 7th transmembrane helix. This may entail the rearrangement of polar species and the shift of macroscopic polarization in the transmembrane domain, triggered by agonist binding. Based on our observations and numerous independent indications, we suggest amending the widely accepted theory that the initiation event of GPCR activation is the shift of macroscopic polarization between the ortho- and allosteric binding pockets and the intracellular G protein-binding interface.

Hemorphins Targeting G Protein-Coupled Receptors

Hemorphins are short peptides produced by the proteolysis of the beta subunit of hemoglobin. These peptides have diverse physiological effects especially in the nervous and the renin-angiotensin systems. Such effects occur through the modulation of a diverse range of proteins including enzymes and receptors. In this review, we focus on pharmacological and functional targeting of G protein-coupled receptors (GPCRs) by hemorphins and their implication in physiology and pathophysiology. Among GPCRs, the opioid receptors constitute the first set of targets of hemorphins with implication in analgesia. Subsequently, several other GPCRs have been reported to be directly or indirectly involved in hemorphins’ action. This includes the receptors for angiotensin II, oxytocin, bombesin, and bradykinin, as well as the human MAS-related G protein-coupled receptor X1. Interestingly, both orthosteric activation and allosteric modulation of GPCRs by hemorphins have been reported. This review links hemorphins with GPCR pharmacology and signaling, supporting the implication of GPCRs in hemorphins’ effects. Thus, this aids a better understanding of the molecular basis of the action of hemorphins and further demonstrates that hemorphin-GPCR axis constitutes a valid target for therapeutic intervention in different systems.

The Effects of Apelin and Elabela Ligands on Apelin Receptor Distinct Signaling Profiles

Apelin and Elabela are endogenous peptide ligands for Apelin receptor (APJ), a widely expressed G protein-coupled receptor. They constitute a spatiotemporal dual ligand system to control APJ signal transduction and function. We investigated the effects of Apelin-13, pGlu₁-apelin-13, Apelin-17, Apelin-36, Elabela-21 and Elabela-32 peptides on APJ signal transduction. Whether different ligands are biased to different APJ mediated signal transduction pathways was studied. We observed the different changes of G protein dependent and β-arrestin dependent signaling pathways after APJ was activated by six peptide ligands. We demonstrated that stimulation with APJ ligands resulted in dose-dependent increases in both G protein dependent [cyclic AMP (cAMP), Ca²⁺ mobilization, and the early phase extracellular related kinase (ERK) activation] and β-arrestin dependent [GRKs, β-arrestin 1, β-arrestin 2, and β2 subunit of the clathrin adaptor AP2] signaling pathways. However, the ligands exhibited distinct signaling profiles. Elabela-32 showed a >1000-fold bias to the β-statin-dependent signaling pathway. These data provide that Apelin-17 was biased toward β-arrestin dependent signaling. Eabela-21 and pGlu₁-Apelin-13 exhibited very distinct activities on the G protein dependent pathway. The activity profiles of these ligands could be valuable for the development of drugs with high selectivity for specific APJ downstream signaling pathways.

Exploring the putative mechanism of allosteric modulations by mixed-action kappa/mu opioid receptor bitopic modulators

The modulation and selectivity mechanisms of seven mixed-action kappa opioid receptor (KOR)/mu opioid receptor (MOR) bitopic modulators were explored. Molecular modeling results indicated that the 'message' moiety of seven bitopic modulators shared the same binding mode with the orthosteric site of the KOR and MOR, whereas the 'address' moiety bound with different subdomains of the allosteric site of the KOR and MOR. The 'address' moiety of seven bitopic modulators bound to different subdomains of the allosteric site of the KOR and MOR may exhibit distinguishable allosteric modulations to the binding affinity and/or efficacy of the 'message' moiety. Moreover, the 3-hydroxy group on the phenolic moiety of the seven bitopic modulators induced selectivity to the KOR over the MOR.

Structural Insights into Ligand-Receptor Interactions Involved in Biased Agonism of G-Protein Coupled Receptors

G protein-coupled receptors (GPCRs) are versatile signaling proteins that mediate complex cellular responses to hormones and neurotransmitters. Ligand directed signaling is observed when agonists, upon binding to the same receptor, trigger significantly different configuration of intracellular events. The current work reviews the structurally defined ligand – receptor interactions that can be related to specific molecular mechanisms of ligand directed signaling across different receptors belonging to class A of GPCRs. Recent advances in GPCR structural biology allow for mapping receptors’ binding sites with residues particularly important in recognition of ligands’ structural features that are responsible for biased signaling. Various studies show particular role of specific residues lining the extended ligand binding domains, biased agonists may alternatively affect their interhelical interactions and flexibility what can be translated into intracellular loop rearrangements. Studies on opioid and angiotensin receptors indicate importance of residues located deeper within the binding cavity and direct interactions with receptor residues linking the ortosteric ligand binding site with the intracellular transducer binding domain. Collection of results across different receptors may suggest elements of common molecular mechanisms which are responsible for passing alternative signals from biased agonists.

Probing biased activation of mu-opioid receptor by the biased agonist PZM21 using all atom molecular dynamics simulation

Morphine is a commonly used opioid drug to treat acute pain by binding to the mu-opioid receptor (MOR), but its effective analgesic efficacy via triggering of the heterotrimeric G_i protein pathway is accompanied by a series of adverse side effects via triggering of the β-arrestin pathway. Recently, PZM21, a recently developed MOR biased agonist, shows preferentially activating the G protein pathway over β-arrestin pathway. However, there is no high-resolution receptor structure in complex with PZM21 and its action mechanism remains elusive. In this study, PZM21 and Morphine were docked to the active human MOR-1 homology structure and then subjected to the molecular dynamics (MD) simulations in two different situations (i.e., one situation includes the crystal waters but another does not). Detailed comparisons between the two systems were made to characterize the differences in protein-ligand interactions, protein secondary and tertiary structures and dynamics networks. PZM21 could strongly interact with Y328^7.43 of TM7, besides the residues (Asp149^3.32 and Tyr150^3.33) of TM3. The two systems' network paths to the intracellular end of TM6 were roughly similar but the paths to the end of TM7 were different. The PZM21-bound MOR's intracellular ends of TM5-7 bent outward more along with the distance changes of the three key molecular switches (ionic lock, transmission and Tyr toggle) and the distance increase of some conserved inter-helical residue pairs. The larger intracellular opening of the receptor could potentially facilitate G protein binding.

Novel Positive Allosteric Modulators of µ Opioid Receptor-Insight from In Silico and In Vivo Studies

Opioids are the drugs of choice in severe pain management. Unfortunately, their use involves serious, potentially lethal side effects. Therefore, efforts in opioid drug design turn toward safer and more effective mechanisms, including allosteric modulation. In this study, molecular dynamics simulations in silico and ‘writhing’ tests in vivo were used to characterize potential allosteric mechanism of two previously reported compounds. The results suggest that investigated compounds bind to μ opioid receptor in an allosteric site, augmenting action of morphine at subeffective doses, and exerting antinociceptive effect alone at higher doses. Detailed analysis of in silico calculations suggests that first of the compounds behaves more like allosteric agonist, while the second compound acts mainly as a positive allosteric modulator.

A single unified model for fitting simple to complex receptor response data

The fitting of complex receptor-response data where fractional response and occupancy do not match is challenging. They encompass important cases including (a) the presence of "receptor reserve" and/or partial agonism, (b) multiple responses assessed at different vantage points along a pathway, (c) responses that are different along diverging downstream pathways (biased agonism), and (d) constitutive activity. For these, simple models such as the well-known Clark or Hill equations cannot be used. Those that can, such as the operational (Black&Leff) model, do not provide a unified approach, have multiple nonintuitive parameters that are challenging to fit in well-defined manner, have difficulties incorporating binding data, and cannot be reduced or connected to simpler forms. We have recently introduced a quantitative receptor model (SABRE) that includes parameters for Signal Amplification (γ), Binding affinity (Kd), Receptor activation Efficacy (ε), and constitutive activity (εR0). It provides a single equation to fit complex cases within a full two-state framework with the possibility of incorporating receptor occupancy data (i.e., experimental Kds). Simpler cases can be fit by using consecutively reduced forms obtained by constraining parameters to specific values, e.g., εR0 = 0: no constitutive activity, γ = 1: no amplification (Emax-type fitting), and ε = 1: no partial agonism (Clark equation). Here, a Hill-type extension is introduced (n ≠ 1), and simulated and experimental receptor-response data from simple to increasingly complex cases are fitted within the unified framework of SABRE with differently constrained parameters.

Molecular Dynamics Simulations to Investigate How PZM21 Affects the Conformational State of the μ-Opioid Receptor Upon Activation

Opioid analgesics such as morphine have indispensable roles in analgesia. However, morphine use can elicit side effects such as respiratory depression and constipation. It has been reported that G protein-biased agonists as substitutes for classic opioid agonists can alleviate (or even eliminate) these side effects. The compounds PZM21 and TRV130 could be such alternatives. Nevertheless, there are controversies regarding the efficacy and G protein-biased ability of PZM21. To demonstrate a rationale for the reduced biasing agonism of PZM21 compared with that of TRV130 at the molecular level, we undertook a long-term molecular dynamics simulation of the μ-opioid receptor (MOR) upon the binding of three ligands: morphine, TRV130, and PZM21. We found that the delayed movement of the W293^6.48 (Ballesteros-Weinstein numbering) side chain was a factor determining the dose-dependent agonism of PZM21. Differences in conformational changes of W318^7.35, Y326^7.43, and Y336^7.53 in PZM21 and TRV130 explained the observed differences in bias between these ligands. The extent of water movements across the receptor channel was correlated with analgesic effects. Taken together, these data suggest that the observed differences in conformational changes of the studied MOR-ligand complexes point to the low-potency and lower bias effects of PZM21 compared with the other two ligands, and they lay the foundation for the development of G protein-biased agonists.

Tuning Down the Pain - An Overview of Allosteric Modulation of Opioid Receptors: Mechanisms of Modulation, Allosteric Sites, Modulator Syntheses

Opioid signaling plays a central role in pain perception. As such, it remains the main target in the development of antinociceptive agents, despite serious side effects involved. In recent years, hopes for improved opioid painkillers are rising, together with our understanding of allosterism and biased signaling mechanisms. In this review, we focus on recently discovered allosteric modulators of opioid receptors, insights into phenomena underlying their action, as well as on how they extend our understanding of mechanisms of previously known compounds. A brief overlook of their synthesis is also presented.

The Use of Computational Approaches in the Discovery and Mechanism Study of Opioid Analgesics

Opioid receptors that belong to class A G protein-coupled receptors (GPCRs) are vital in pain control. In the past few years, published high-resolution crystal structures of opioid receptor laid a solid basis for both experimental and computational studies. Computer-aided drug design (CADD) has been established as a powerful tool for discovering novel lead compounds and for understanding activation mechanism of target receptors. Herein, we reviewed the computational-guided studies on opioid receptors for the discovery of new analgesics, the structural basis of receptor subtype selectivity, agonist interaction mechanism, and biased signaling mechanism.

Endogenous opiates and behavior: 2017

This paper is the fortieth consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2017 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Molecular insights into the interaction of hemorphin and its targets

Hemorphins are atypical endogenous opioid peptides produced by the cleavage of hemoglobin beta chain. Several studies have reported the therapeutic potential of hemorphin in memory enhancement, blood regulation, and analgesia. However, the mode of interaction of hemorphin with its target remains largely elusive. The decapeptide LVV-hemorphin-7 is the most stable form of hemorphin. It binds with high affinity to mu-opioid receptors (MOR), angiotensin-converting enzyme (ACE) and insulin-regulated aminopeptidase (IRAP). In this study, computational methods were used extensively to elucidate the most likely binding pose of mammalian LVV-hemorphin-7 with the aforementioned proteins and to calculate the binding affinity. Additionally, alignment of mammalian hemorphin sequences showed that the hemorphin sequence of the camel harbors a variation - a Q > R substitution at position 8. This study also investigated the binding affinity and the interaction mechanism of camel LVV-hemorphin-7 with these proteins. To gain a better understanding of the dynamics of the molecular interactions between the selected targets and hemorphin peptides, 100 ns molecular dynamics simulations of the best-ranked poses were performed. Simulations highlighted major interactions between the peptides and key residues in the binding site of the proteins. Interestingly, camel hemorphin had a higher binding affinity and showed more interactions with all three proteins when compared to the canonical mammalian LVV-hemorphin-7. Thus, camel LVV-hemorphin-7 could be explored as a potent therapeutic agent for memory loss, hypertension, and analgesia.

The Universal 3D QSAR Model for Dopamine D2 Receptor Antagonists

In order to search for novel antipsychotics acting through the D₂ receptor, it is necessary to know the structure–activity relationships for dopamine D₂ receptor antagonists. In this context, we constructed the universal three-dimensional quantitative structure–activity relationship (3D- QSAR) model for competitive dopamine D₂ receptor antagonists. We took 176 compounds from chemically different groups characterized by the half maximal inhibitory concentration (IC₅₀)from the CHEMBL database and docked them to the X-ray structure of the human D₂ receptor in the inactive state. Selected docking poses were applied for Comparative Molecular Field Analysis (CoMFA) alignment. The obtained CoMFA model is characterized by a cross-validated coefficient Q² of 0.76 with an optimal component of 5, R² of 0.92, and an F value of 338.9. The steric and electrostatic field contributions are 67.4% and 32.6%, respectively. The statistics obtained prove that the CoMFA model is significant. Next, the IC₅₀ of the 16 compounds from the test set was predicted with R² of 0.95. Finally, a progressive scrambling test was carried out for additional validation. The CoMFA fields were mapped onto the dopamine D₂ receptor binding site, which enabled a discussion of the structure–activity relationship based on ligand–receptor interactions. In particular, it was found that one of the desired steric interactions covers the area of a putative common allosteric pocket suggested for some other G protein-coupled receptors (GPCRs), which would suggest that some of the known dopamine receptor antagonists are bitopic in their essence. The CoMFA model can be applied to predict the potential activity of novel dopamine D₂ receptor antagonists.

A Receptor Model With Binding Affinity, Activation Efficacy, and Signal Amplification Parameters for Complex Fractional Response Versus Occupancy Data

In quantitative pharmacology, multi-parameter receptor models are needed to account for the complex nonlinear relationship between fractional occupancy and response that can occur due to the intermixing of the effects of partial receptor activation and post-receptor signal amplification. Here, a general two-state receptor model and corresponding quantitative forms are proposed that unify three distinct processes, each characterized with its own parameter: 1) receptor binding, characterized by K_d, the equilibrium dissociation constant used for binding affinity; 2) receptor activation, characterized by an (intrinsic) efficacy parameter ε; and 3) post-activation signal transduction (amplification), characterized by a gain parameter γ. Constitutive activity is accommodated via an additional ε_R0 parameter quantifying the activation of the ligand-free receptor. Receptors can be active or inactive in both their ligand-free and ligand-bound states (two-state receptor theory), but ligand binding alters the likelihood of activation (induced fit). Because structural data now confirm that for most receptors in their active conformation, the small-molecule ligand-binding site is buried inside, straightforward binding to the active form (direct conformational selection) is unlikely. The proposed general equation has parameters that are more intuitive and better suited for optimization by nonlinear regression than those of the operational (Black and Leff) or del Castillo–Katz model. The model provides a unified framework for fitting complex data including a) fractional responses that do not match independently measured fractional occupancies, b) responses measured after partial irreversible inactivation of the “receptor reserve” (Furchgott method), c) fractional responses that are different along distinct downstream pathways (biased agonism), and d) responses with constitutive receptor activity. Furthermore, unlike previous models, the present one can be reduced back for special cases of its parameters to consecutively nested simplified forms that can be used on their own when adequate (e.g., ε_R0 = 0, no constitutive activity; γ = 1: E_max model for partial agonism; ε = 1: Clark equation).

A Biased View of μ-Opioid Receptors?

The field of biased agonism has grown substantially in recent years and the μ-opioid receptor has been one of the most intensively studied receptor targets for developing biased agonists. Yet, despite extensive research efforts, the development of analgesics with reduced adverse effects remains a significant challenge. In this review we discuss the evidence to support the prevailing hypothesis that a G protein-biased agonist at the μ-opioid receptor would be an effective analgesic without the accompanying adverse effects associated with conventional μ-opioid agonists. We also assess the current status of established and novel μ-opioid-receptor ligands that are proposed to be biased ligands. SIGNIFICANCE STATEMENT: The idea that biased agonists at the μ-opioid receptor might provide a therapeutic advantage in terms of producing effective analgesia with fewer adverse effects has driven the design of novel G protein-biased agonists. However, is the desirability of G protein-biased agonists at μ-opioid receptor substantiated by what we know of the physiology and pharmacology of the receptor? Also, do any of the novel biased agonists live up to their initial promise? Here we address these issues by critically examining the evidence that G protein bias really is desirable and also by discussing whether the ligands so far developed are clearly biased in vitro and whether this produces responses in vivo that might be commensurate with such bias.

Biased signaling of G protein coupled receptors (GPCRs): Molecular determinants of GPCR/transducer selectivity and therapeutic potential

G protein coupled receptors (GPCRs) convey signals across membranes via interaction with G proteins. Originally, an individual GPCR was thought to signal through one G protein family, comprising cognate G proteins that mediate canonical receptor signaling. However, several deviations from canonical signaling pathways for GPCRs have been described. It is now clear that GPCRs can engage with multiple G proteins and the line between cognate and non-cognate signaling is increasingly blurred. Furthermore, GPCRs couple to non-G protein transducers, including β-arrestins or other scaffold proteins, to initiate additional signaling cascades. Receptor/transducer selectivity is dictated by agonist-induced receptor conformations as well as by collateral factors. In particular, ligands stabilize distinct receptor conformations to preferentially activate certain pathways, designated 'biased signaling'. In this regard, receptor sequence alignment and mutagenesis have helped to identify key receptor domains for receptor/transducer specificity. Furthermore, molecular structures of GPCRs bound to different ligands or transducers have provided detailed insights into mechanisms of coupling selectivity. However, receptor dimerization, compartmentalization, and trafficking, receptor-transducer-effector stoichiometry, and ligand residence and exposure times can each affect GPCR coupling. Extrinsic factors including cell type or assay conditions can also influence receptor signaling. Understanding these factors may lead to the development of improved biased ligands with the potential to enhance therapeutic benefit, while minimizing adverse effects. In this review, evidence for ligand-specific GPCR signaling toward different transducers or pathways is elaborated. Furthermore, molecular determinants of biased signaling toward these pathways and relevant examples of the potential clinical benefits and pitfalls of biased ligands are discussed.

Emerging Insights into Mu Opioid Pharmacology

Opioid analgesics, most of which act through mu opioid receptors, have long represented valuable therapeutic agents to treat severe pain. Concerted drug development efforts for over a 100 years have resulted in a large variety of opioid analgesics used in the clinic, but all of them continue to exhibit the side effects, especially respiratory depression, that have long plagued the use of morphine. The recent explosion in fatalities resulting from overdose of prescription and synthetic opioids has dramatically increased the need for safer analgesics, but recent developments in mu receptor research have provided new strategies to develop such drugs. This chapter reviews recent advances in developing novel opioid analgesics from an understanding of mu receptor structure and function. This includes a summary of the mechanism of agonist binding deduced from the crystal structure of mu receptors. It will also highlight the development of novel agonist mechanisms, including biased agonists, bivalent ligands, and allosteric modulators of mu receptor function, and describe how receptor phosphorylation modulates these pathways. Finally, it will summarize research on the alternative pre-mRNA splicing mechanisms that produces a multiplicity of mu receptor isoforms. Many of these isoforms exhibit different pharmacological specificities and brain circuitry localization, thus providing an opportunity to develop novel drugs with increased therapeutic windows.

To probe interaction of morphine and IBNtxA with 7TM and 6TM variants of the human μ-opioid receptor using all-atom molecular dynamics simulations with an explicit membrane

IBNtxA, a morphine derivative, is 10-fold more potent and has a better safety profile than morphine. Animal studies indicate that the analgesic effect of IBNtxA appears to be mediated by the activation of truncated splice variants (6TM) of the Mu opioid receptor (MOR-1) where transmembrane helix 1 (TM1) is removed. Interestingly, morphine is unable to activate 6TM variants. To date, a high resolution structure of 6TM variants is missing, and the interaction of 6TM variants with IBNtxA and morphine remains elusive. In this study we used homology modeling, docking and molecular dynamics (MD) simulations to study a representative 6TM variant (G1) and a full-length 7TM variant of human MOR-1 in complex with IBNtxA and morphine respectively. The structural models of human G1 and 7TM were obtained by homology modeling using the X-ray solved crystal structure of the active mouse 7TM bound to an agonist BU72 (PDB id: ) as the template. Our 6000 ns MD data show that either TM1 truncation (i.e. from 7TM to 6TM) or ligand modification (i.e. from morphine to IBNtxA) alone causes the loss of key morphine-7TM interactions that are well-known to be required for MOR-1 activation. Receptor disruptions are mainly located at TMs 2, 3, 6 and 7 in comparison with the active crystal complex. However, when both perturbations occur in the 6TM-IBNtxA complex, the key ligand-receptor interactions and the receptor conformation are recovered to resemble those in the active 7TM-morphine complex. Our molecular switch analysis further explains well why morphine is not able to activate 6TM variants. The close resemblance between 6TM-IBTtxA and 7TM in complex with PZM21, a G-protein biased 7TM agonist, suggests the possible biased agonism of IBNtxA on G1, which is consistent with its reduced side effects.

Insights from molecular dynamics simulations to exploit new trends for the development of improved opioid drugs

Having accidental deaths from opioid overdoses almost quadrupled over the past fifteen years, there is a strong need to develop new, non-addictive medications for chronic pain to stop one of the deadliest epidemics in American history. Given their potentially fewer on-target overdosing risks and other adverse effects compared to classical opioid drugs, attention has recently shifted to opioid allosteric modulators and G protein-biased opioid agonists as likely drug candidates to prevent and/or reverse opioid overdoses. Understanding how these molecules bind and activate their receptors at an atomistic level is key to developing them into effective new therapeutics, and molecular dynamics-based strategies are contributing tremendously to this understanding.

Computational insights into the G-protein-biased activation and inactivation mechanisms of the μ opioid receptor

The μ opioid receptor (OR), a member of the class A subfamily of G-protein coupled receptors (GPCRs), is a major target for the treatment of pain. G-protein biased μ-OR agonists promise to be developed as analgesics. Thus, TRV130, the first representative μ-OR ligand with G-protein bias, has entered into phase III clinical trials. To identify the detailed G-protein-biased activation and inactivation mechanisms of the μ-OR, we constructed five μ-OR systems that were in complexes with the G-protein-biased agonists TRV130 and BU72, the antagonists β-FNA and naltrexone, as well as the free receptor. We performed a series of conventional molecular dynamics simulations and analyses of G-protein-biased activation and inactivation mechanisms of μ-OR. Our results, together with previously reported mutation results, revealed the operating mode of the activation switch composed of residues W^6.48 and Y^7.43 (Ballesteros/Weinstein numbering), the activity of which was responsible for down- and up-regulation, respectively, of the β-arrestin signaling, which in turn affected G-protein-biased activation of μ-OR. TRV130 was found to stabilize W^6.48 by interacting with Y^7.43. In addition, we obtained useful information regarding μ-OR-biased activation, such as strong stabilization of W^7.35 through a hydrophobic ring interaction in the TRV130 system. These findings may facilitate understanding of μ-OR biased activation and the design of new biased ligands for GPCRs.

Dynamic and Kinetic Elements of µ-Opioid Receptor Functional Selectivity

While the therapeutic effect of opioids analgesics is mainly attributed to µ-opioid receptor (MOR) activation leading to G protein signaling, their side effects have mostly been linked to β-arrestin signaling. To shed light on the dynamic and kinetic elements underlying MOR functional selectivity, we carried out close to half millisecond high-throughput molecular dynamics simulations of MOR bound to a classical opioid drug (morphine) or a potent G protein-biased agonist (TRV-130). Statistical analyses of Markov state models built using this large simulation dataset combined with information theory enabled, for the first time: a) Identification of four distinct metastable regions along the activation pathway, b) Kinetic evidence of a different dynamic behavior of the receptor bound to a classical or G protein-biased opioid agonist, c) Identification of kinetically distinct conformational states to be used for the rational design of functionally selective ligands that may eventually be developed into improved drugs; d) Characterization of multiple activation/deactivation pathways of MOR, and e) Suggestion from calculated transition timescales that MOR conformational changes are not the rate-limiting step in receptor activation.

Signaling within Allosteric Machines: Signal Transmission Pathways Inside G Protein-Coupled Receptors

In recent years, our understanding of function of G protein-coupled receptors (GPCRs) has changed from a picture of simple signal relays, transmitting only a particular signal to a particular G protein heterotrimer, to versatile machines, capable of various responses to different stimuli and being modulated by various factors. Some recent reports provide not only the data on ligands/modulators and resultant signals induced by them, but also deeper insights into exact pathways of signal migration and mechanisms of signal transmission through receptor structure. Combination of these computational and experimental data sheds more light on underlying mechanisms of signal transmission and signaling bias in GPCRs. In this review we focus on available clues on allosteric pathways responsible for complex signal processing within GPCRs structures, with particular emphasis on linking compatible in silico- and in vitro-derived data on the most probable allosteric connections.