ERNEST COST action overview on the (patho)physiology of GPCRs and orphan GPCRs in the nervous system.

G protein-coupled receptors (GPCRs) are a large family of cell surface receptors that play a critical role in nervous system function by transmitting signals between cells and their environment. They are involved in many, if not all, nervous system processes, and their dysfunction has been linked to various neurological disorders representing important drug targets. This overview emphasises the GPCRs of the nervous system, which are the research focus of the members of ERNEST COST action (CA18133) working group 'Biological roles of signal transduction'. First, the (patho)physiological role of the nervous system GPCRs in the modulation of synapse function is discussed. We then debate the (patho)physiology and pharmacology of opioid, acetylcholine, chemokine, melatonin and adhesion GPCRs in the nervous system. Finally, we address the orphan GPCRs, their implication in the nervous system function and disease, and the challenges that need to be addressed to deorphanize them.

Time-dependent ligand-receptor binding kinetics and functionality in a heterodimeric receptor model.

GPCRs heteromerize both in CNS and non-CNS regions. The cell uses receptor heteromerization to modulate receptor functionality and to provide fine tuning of receptor signaling. In order for pharmacologists to explore these mechanisms for therapeutic purposes, quantitative receptor models are needed. We have developed a time-dependent model of the binding kinetics and functionality of a preformed heterodimeric receptor involving two drugs. Two cases were considered: both or only one of the drugs are in excess with respect to the total concentration of the receptor. The latter case can be applied to those situations in which a drug causes unwanted side effects that need to be reduced by decreasing its concentration. The required efficacy can be maintained by the allosteric effects mutually exerted by the two drugs in the two-drug combination system. We discuss this concept assuming that the drug causing unwanted side effects is an opioid and that analgesia is the therapeutic effect. As additional points, allosteric modulation by endogenous compounds and synthetic bivalent ligands was included in the study. Receptor heteromerization offers a mechanistic understanding and quantification of the pharmacological effects elicited by combinations of two drugs at different doses and with different efficacies and cooperativity effects, thus providing a conceptual framework for drug combination therapy.

Factors associated with the intensity of anxiety and depression symptoms in health workers of two centres of reference for COVID 19 patient care in Antioquia, Colombia - A latent class analysis.

OBJECTIVE: To classify the staff of two reference institutions for COVID-19 care in Antioquia according to the intensity of anxiety and depression symptoms, and to determine the factors associated with these classes. METHODS: Cross-sectional study in which the GAD-7, PHQ-9, fear of COVID-19, and the Copenhagen Burnout scale were used. Latent class analysis was performed to identify the classes, and the factors associated with these were determined using multinomial logistic regression. RESULTS: 486 people participated. The three-class model had the best fit: class I with low scores on the scales; class II with mild degrees of anxiety and depression, and intermediate levels of fear of COVID-19 and perceived stress; and class III with moderate and severe degrees of anxiety, depression, and perceived stress. The factors associated with belonging to class III were age (OR = 0.94; 95%CI, 0.91-0.96), change of residence to avoid exposing relatives (OR = 4.01; 95%CI, 1.99-8.09), and a history of depressive disorder (OR = 3.10; 95%CI, 1.27-7.56), and anxiety (OR = 5.5; 95%CI, 2.36-12.90). Factors associated with class II were age (OR = 0.97; 95%CI, 0.95-0.99), history of depressive disorder (OR = 3.41; 95%CI, 1.60-7.25), living with someone at risk of death from COVID-19 (OR = 1.86; 95%CI, 1.19-2.91), family member being healthcare staff (OR = 1.58; 95%CI, 1.01-2.47), and change of residence to avoid exposing relatives (OR = 1.99; 95%CI, 1.11-3.59). CONCLUSIONS: Three classes of participants were obtained, two of them with anxiety and depression symptoms. Younger age and a history of mental disorder were factors associated with the two classes of symptomatic patients; other factors may be causes or consequences of the symptoms.

A 19F-qNMR-Guided Mathematical Model for G Protein-Coupled Receptor Signaling.

G protein-coupled receptors (GPCRs) exhibit a wide range of pharmacological efficacies, yet the molecular mechanisms responsible for the differential efficacies in response to various ligands remain poorly understood. This lack of understanding has hindered the development of a solid foundation for establishing a mathematical model for signaling efficacy. However, recent progress has been made in delineating and quantifying receptor conformational states and associating function with these conformations. This progress has allowed us to construct a mathematical model for GPCR signaling efficacy that goes beyond the traditional ON/OFF binary switch model. In this study, we present a quantitative conformation-based mathematical model for GPCR signaling efficacy using the adenosine A2A receptor (A2AR) as a model system, under the guide of 19F quantitative nuclear magnetic resonance experiments. This model encompasses two signaling states, a fully activated state and a partially activated state, defined as being able to regulate the cognate Gα s nucleotide exchange with respective G protein recognition capacity. By quantifying the population distribution of each state, we can now in turn examine GPCR signaling efficacy. This advance provides a foundation for assessing GPCR signaling efficacy using a conformation-based mathematical model in response to ligand binding. SIGNIFICANCE STATEMENT: Mathematical models to describe signaling efficacy of GPCRs mostly suffer from considering only two states (ON/OFF). However, research indicates that a GPCR possesses multiple active-(like) states that can interact with Gαßγ independently, regulating varied nucleotide exchanges. With the guide of 19F-qNMR, the transitions among these states are quantified as a function of ligand and Gαßγ, serving as a foundation for a novel conformation-based mathematical signaling model.

Remote local photoactivation of morphine produces analgesia without opioid-related adverse effects.

BACKGROUND AND PURPOSE: Opioid-based drugs are the gold standard medicines for pain relief. However, tolerance and several side effects (i.e. constipation and dependence) may occur upon chronic opioid administration. Photopharmacology is a promising approach to improve the benefit/risk profiles of these drugs. Thus, opioids can be locally activated with high spatiotemporal resolution, potentially minimizing systemic-mediated adverse effects. Here, we aimed at developing a morphine photo-derivative (photocaged morphine), which can be activated upon light irradiation both in vitro and in vivo. EXPERIMENTAL APPROACH: Light-dependent activity of pc-morphine was assessed in cell-based assays (intracellular calcium accumulation and electrophysiology) and in mice (formalin animal model of pain). In addition, tolerance, constipation and dependence were investigated in vivo using experimental paradigms. KEY RESULTS: In mice, pc-morphine was able to elicit antinociceptive effects, both using external light-irradiation (hind paw) and spinal cord implanted fibre-optics. In addition, remote morphine photoactivation was devoid of common systemic opioid-related undesired effects, namely, constipation, tolerance to the analgesic effects, rewarding effects and naloxone-induced withdrawal. CONCLUSION AND IMPLICATIONS: Light-dependent opioid-based drugs may allow effective analgesia without the occurrence of tolerance or the associated and severe opioid-related undesired effects. LINKED ARTICLES: This article is part of a themed issue on Advances in Opioid Pharmacology at the Time of the Opioid Epidemic. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v180.7/issuetoc.

Allosteric binding cooperativity in a kinetic context.

Allosteric modulators are of prime interest in drug discovery. These drugs regulate the binding and function of endogenous ligands, with some advantages over orthosteric ligands. A typical pharmacological parameter in allosteric modulation is binding cooperativity. This property can yield unexpected but illuminating results when decomposed into its kinetic parameters. Using two reference models (the allosteric ternary complex receptor model and a heterodimer receptor model), a relationship has been derived for the cooperativity rate constant parameters. This relationship allows many combinations of the cooperativity kinetic parameters for a single binding cooperativity value obtained under equilibrium conditions. This assessment may help understand striking experimental results involving allosteric modulation and suggest further investigations in the field.

Evaluating Allosteric Perturbations in Cannabinoid Receptor 1 by In Silico Single-Point Mutation.

Cannabinoid receptor 1 (CB1) is a promising drug target involved in many physiological processes. Using atomistic molecular dynamics (MD) simulations, we examined the structural effect of F237L mutation on CB1, a mutation that has qualitatively similar effects to allosteric ligand ORG27569 binding. This mutation showed a global effect on CB1 conformations. Among the observed effects, TM6 outward movement and the conformational change of the NPxxY motif upon receptor activation by CB1 agonist CP55940 were hindered compared to wt CB1. Within the orthosteric binding site, CP55940 interactions with CB1 were altered. Our results revealed that allosteric perturbations introduced by the mutation had a global impact on receptor conformations, suggesting that the mutation site is a key region for allosteric modulation in CB1.

In Silico Assessment of the Lipid Fingerprint Signature of ATP2, the Essential P4-ATPase of Malaria Parasites.

ATP2, a putative type 4 P-type ATPase, is a phosphatidylinositol-4-phosphate (PI4P)-regulated phospholipid transporter with an interesting potential as an antimalarial drug target due to its conservation across Plasmodium species and its essential role in the life cycle of Plasmodium falciparum. Despite its importance, the exact mechanism of its action and regulation is still not fully understood. In this study we used coarse-grained molecular dynamics (CG-MD) to elucidate the lipid-protein interactions between a heterogeneous lipid membrane containing phosphatidylinositol and Plasmodium chabaudi ATP2 (PcATP2), an ortholog of P. falciparum ATP2. Our study reveals structural information of the lipid fingerprint of ATP2, and provides structural information on the potential phosphatidylinositol allosteric binding site. Moreover, we identified a set of evolutionary conserved residues that may play a key role in the binding and stabilization of lipids in the binding pocket.

Spontaneous changes in brain striatal dopamine synthesis and storage dynamics ex vivo reveal end-product feedback-inhibition of tyrosine hydroxylase.

Synaptic events are important to define treatment strategies for brain disorders. In the present paper, freshly obtained rat brain striatal minces were incubated under different times and conditions to determine dopamine biosynthesis, storage, and tyrosine hydroxylase phosphorylation. Remarkably, we found that endogenous dopamine spontaneously accumulated during tissue incubation at 37 °C ex vivo while dopamine synthesis simultaneously decreased. We analyzed whether these changes in brain dopamine biosynthesis and storage were linked to dopamine feedback inhibition of its synthesis-limiting enzyme tyrosine hydroxylase. The aromatic-l-amino-acid decarboxylase inhibitor NSD-1015 prevented both effects. As expected, dopamine accumulation was increased with l-DOPA addition or VMAT2-overexpression, and dopamine synthesis decreased further with added dopamine, the VMAT2 inhibitor tetrabenazine or D2 auto-receptor activation with quinpirole, accordingly to the known synaptic effects of these treatments. Phosphorylation activation and inhibition of tyrosine hydroxylase on Ser31 and Ser40 with okadaic acid, Sp-cAMP and PD98059 also exerted the expected effects. However, no clear-cut association was found between dopamine feedback inhibition of its own biosynthesis and changes of tyrosine hydroxylase phosphorylation, assessed by Western blot and mass spectrometry. The later technique also revealed a new Thr30 phosphorylation in rat tyrosine hydroxylase. Our methodological assessment of brain dopamine synthesis and storage dynamics ex vivo could be applied to predict the in vivo effects of pharmacological interventions in animal models of dopamine-related disorders.

[Factors associated with the intensity of anxiety and depression symptoms in health workers of two centres of reference for COVID 19 patient care in Antioquia, Colombia - a latent class analysis]. / Factores asociados con la intensidad de los síntomas ansiosos y depresivos en personal de salud de dos centros de referencia para la atención de pacientes con COVID-19 de Antioquia, Colombia. Un análisis de clases latentes.

Objective: To classify the staff of two reference institutions for COVID-19 care in Antioquia according to the intensity of anxiety and depression symptoms, and to determine the factors associated with these classes.Methods:Cross-sectional study in which the GAD-7, PHQ-9, fear of COVID-19, and the Copenhagen Burnout scale were used. Latent class analysis was performed to identify the classes, and the factors associated with these were determined using multinomial logistic regression.Results: 486 people participated. The three-class model had the best fit: class I with low scores on the scales; class II with mild degrees of anxiety and depression, and intermediate levels of fear of COVID-19 and perceived stress; and class III with moderate and severe degrees of anxiety, depression, and perceived stress. The factors associated with belonging to class III were age (OR=0.94; 95%CI, 0.91-0.96), change of residence to avoid exposing relatives (OR=4.01; 95%CI, 1.99-8.09), and a history of depressive disorder (OR=3.10; 95%CI, 1.27-7.56), and anxiety (OR=5.5; 95%CI, 2.36-12.90). Factors associated with class II were age (OR=0.97; 95%CI, 0.95-0.99), history of depressive disorder (OR=3.41; 95%CI, 1.60-7.25), living with someone at risk of death from COVID-19 (OR=1.86; 95%CI, 1.19-2.91), family member being healthcare staff (OR=1.58; 95%CI, 1.01-2.47), and change of residence to avoid exposing relatives (OR=1.99; 95%CI, 1.11-3.59).Conclusions: Three classes of participants were obtained, two of them with anxiety and depression symptoms. Younger age and a history of mental disorder were factors associated with the two classes of symptomatic patients; other factors may be causes or consequences of the symptoms.

Discovery of a true bivalent dopamine D2 receptor agonist.

Employing two different alkyne-modified dopamine agonists to construct bivalent compounds via click chemistry resulted in the identification of a bivalent ligand (11c) for dopamine D2 receptor homodimer, which, compared to its parent monomeric alkyne, showed a 16-fold higher binding affinity for the dopamine D2 receptor and a 5-fold higher potency in a cAMP assay in HEK 293T cells stably expressing D2R. Molecular modeling revealed that 11c can indeed bridge the orthosteric binding sites of a D2R homodimer in a relaxed conformation via the TM5-TM6 interface and allows to largely rationalize the results of the receptor assays.

Structural Assessment of Agonist Efficacy in the µ-Opioid Receptor: Morphine and Fentanyl Elicit Different Activation Patterns.

Over the past two decades, the opioid epidemic in the United States and Canada has evidenced the need for a better understanding of the molecular mechanisms of medications used to fight pain. Morphine and fentanyl are widely used in opiate-mediated analgesia for the treatment of chronic pain. These compounds target the µ-opioid receptor (MOR), a class A G protein-coupled receptor (GPCR). In light of described higher efficacy of fentanyl with respect to morphine, we have performed independent µs-length unbiased molecular dynamics (MD) simulations of MOR complexes with each of these ligands, including the MOR antagonist naltrexone as a negative control. Consequently, MD simulations totaling 58 µs have been conducted to elucidate at the atomic level ligand-specific receptor activity and signal transmission in the MOR. In particular, we have identified stable binding poses of morphine and fentanyl, which interact differently with the MOR. Different ligand-receptor interaction landscapes directly induce sidechain conformational changes of orthosteric pocket residues: Asp1493.32, Tyr1503.33, Gln1262.60, and Lys2355.39. The induced conformations determine Asp1493.32-Tyr3287.43 sidechain-sidechain interactions and Trp2956.48-Ala2425.46 sidechain-backbone H-bond formations, as well as Met1533.36 conformational changes. In addition to differences in ligand binding, different intracellular receptor conformational changes are observed as morphine preferentially activates transmembrane (TM) helices: TM3 and TM5, while fentanyl preferentially activates TM6 and TM7. As conformational changes in TM6 and TM7 are widely described as being the most crucial aspect in GPCR activation, this may contribute to the greater efficacy of fentanyl over morphine. These computationally observed functional differences between fentanyl and morphine may provide new avenues for the design of safer but not weaker opioid drugs because it is desirable to increase the safety of medicines without sacrificing their efficacy.

Dynamical Correlations Reveal Allosteric Sites in G Protein-Coupled Receptors.

G protein-coupled Receptors (GPCRs) play a central role in many physiological processes and, consequently, constitute important drug targets. In particular, the search for allosteric drugs has recently drawn attention, since they could be more selective and lead to fewer side effects. Accordingly, computational tools have been used to estimate the druggability of allosteric sites in these receptors. In spite of many successful results, the problem is still challenging, particularly the prediction of hydrophobic sites in the interface between the protein and the membrane. In this work, we propose a complementary approach, based on dynamical correlations. Our basic hypothesis was that allosteric sites are strongly coupled to regions of the receptor that undergo important conformational changes upon activation. Therefore, using ensembles of experimental structures, normal mode analysis and molecular dynamics simulations we calculated correlations between internal fluctuations of different sites and a collective variable describing the activation state of the receptor. Then, we ranked the sites based on the strength of their coupling to the collective dynamics. In the ß2 adrenergic (ß2AR), glucagon (GCGR) and M2 muscarinic receptors, this procedure allowed us to correctly identify known allosteric sites, suggesting it has predictive value. Our results indicate that this dynamics-based approach can be a complementary tool to the existing toolbox to characterize allosteric sites in GPCRs.

Statistics for the analysis of molecular dynamics simulations: providing P values for agonist-dependent GPCR activation.

Molecular dynamics (MD) is the common computational technique for assessing efficacy of GPCR-bound ligands. Agonist efficacy measures the capability of the ligand-bound receptor of reaching the active state in comparison with the free receptor. In this respect, agonists, neutral antagonists and inverse agonists can be considered. A collection of MD simulations of both the ligand-bound and the free receptor are needed to provide reliable conclusions. Variability in the trajectories needs quantification and proper statistical tools for meaningful and non-subjective conclusions. Multiple-factor (time, ligand, lipid) ANOVA with repeated measurements on the time factor is proposed as a suitable statistical method for the analysis of agonist-dependent GPCR activation MD simulations. Inclusion of time factor in the ANOVA model is consistent with the time-dependent nature of MD. Ligand and lipid factors measure agonist and lipid influence on receptor activation. Previously reported MD simulations of adenosine A2a receptor (A2aR) are reanalyzed with this statistical method. TM6-TM3 and TM7-TM3 distances are selected as dependent variables in the ANOVA model. The ligand factor includes the presence or absence of adenosine whereas the lipid factor considers DOPC or DOPG lipids. Statistical analysis of MD simulations shows the efficacy of adenosine and the effect of the membrane lipid composition. Subsequent application of the statistical methodology to NECA A2aR agonist, with resulting P values in consistency with its pharmacological profile, suggests that the method is useful for ligand comparison and potentially for dynamic structure-based virtual screening.

Insights into adenosine A2A receptor activation through cooperative modulation of agonist and allosteric lipid interactions.

The activation process of G protein-coupled receptors (GPCRs) has been extensively studied, both experimentally and computationally. In particular, Molecular Dynamics (MD) simulations have proven useful in exploring GPCR conformational space. The typical behaviour of class A GPCRs, when subjected to unbiased MD simulations from their crystallized inactive state, is to fluctuate between inactive and intermediate(s) conformations, even with bound agonist. Fully active conformation(s) are rarely stabilized unless a G protein is also bound. Despite several crystal structures of the adenosine A2a receptor (A2aR) having been resolved in complex with co-crystallized agonists and Gs protein, its agonist-mediated activation process is still not completely understood. In order to thoroughly examine the conformational landscape of A2aR activation, we performed unbiased microsecond-length MD simulations in quadruplicate, starting from the inactive conformation either in apo or with bound agonists: endogenous adenosine or synthetic NECA, embedded in two homogeneous phospholipid membranes: 1,2-dioleoyl-sn-glycerol-3-phosphoglycerol (DOPG) or 1,2-dioleoyl-sn-glycerol-3-phosphocholine (DOPC). In DOPC with bound adenosine or NECA, we observe transition to an intermediate receptor conformation consistent with the known adenosine-bound crystal state. In apo state in DOPG, two different intermediate conformations are obtained. One is similar to that observed with bound adenosine in DOPC, while the other is closer to the active state but not yet fully active. Exclusively, in DOPG with bound adenosine or NECA, we reproducibly identify receptor conformations with fully active features, which are able to dock Gs protein. These different receptor conformations can be attributed to the action/absence of agonist and phospholipid-mediated allosteric effects on the intracellular side of the receptor.

Exploring the Activation Mechanism of the mGlu5 Transmembrane Domain.

As a class C GPCR and regulator of synaptic activity, mGlu5 is an attractive drug target, potentially offering treatment for several neurologic and psychiatric disorders. As little is known about the activation mechanism of mGlu5 at a structural level, potential of mean force calculations linked to molecular dynamics simulations were performed on the mGlu5 transmembrane domain crystal structure to explore various internal mechanisms responsible for its activation. Our results suggest that the hydrophilic interactions between intracellular loop 1 and the intracellular side of TM6 have to be disrupted to reach a theoretically active-like conformation. In addition, interactions between residues that are key for mGlu5 activation (Tyr6593.44 and Ile7515.51) and mGlu5 inactivation (Tyr6593.44 and Ser8097.39) have been identified. Inasmuch as mGlu5 receptor signaling is poorly understood, potentially showing a complex network of micro-switches and subtle structure-activity relationships, the present study represents a step forward in the understanding of mGlu5 transmembrane domain activation.

Evaluation of Operational Models of Agonism and Allosterism at Receptors with Multiple Orthosteric Binding Sites.

Current operational models of agonism and allosterism quantify ligand actions at receptors where agonist concentration-response relationships are nonhyperbolic by introduction of a transducer slope that relates receptor occupancy to response. However, for some receptors nonhyperbolic concentration-response relationships arise from multiple endogenous agonist molecules binding to a receptor in a cooperative manner. Thus, we developed operational models of agonism in systems with cooperative agonist binding and evaluated the models by simulating data describing agonist effects. The models were validated by analyzing experimental data demonstrating the effects of agonists and allosteric modulators at receptors where agonist binding follows hyperbolic (M4 muscarinic acetylcholine receptors) or nonhyperbolic relationships (metabotropic glutamate receptor 5 and calcium-sensing receptor). For hyperbolic agonist concentration-response relationships, no differences in estimates of ligand affinity, efficacy, or cooperativity were observed when the slope was assigned to either a transducer slope or agonist binding slope. In contrast, for receptors with nonhyperbolic agonist concentration-response relationships, estimates of ligand affinity, efficacy, or cooperativity varied depending on the assignment of the slope. The extent of this variation depended on the magnitude of the slope value and agonist efficacy, and for allosteric modulators on the magnitude of cooperativity. The modified operational models described herein are well suited to analyzing agonist and modulator interactions at receptors that bind multiple orthosteric agonists in a cooperative manner. Accounting for cooperative agonist binding is essential to accurately quantify agonist and drug actions. SIGNIFICANCE STATEMENT: Some orthosteric agonists bind to multiple sites on a receptor, but current analytical methods to characterize such interactions are limited. Herein, we develop and validate operational models of agonism and allosterism for receptors with multiple orthosteric binding sites, and demonstrate that such models are essential to accurately quantify agonist and drug actions. These findings have important implications for the discovery and development of drugs targeting receptors such as the calcium-sensing receptor, which binds at least five calcium ions.

Artificial Intelligence: A Novel Approach for Drug Discovery.

Molecular dynamics (MD) simulations can mechanistically explain receptor function. However, the enormous data sets that they may imply can be a hurdle. Plante and colleagues (Molecules, 2019) recently described a machine learning approach to the analysis of MD simulations. The approach successfully classified ligands and identified functional receptor motifs and thus it seems promising for mechanism-based drug discovery.

Revealing the Mechanism of Agonist-Mediated Cannabinoid Receptor 1 (CB1) Activation and Phospholipid-Mediated Allosteric Modulation.

Cannabinoid receptor 1 (CB1) mediates the functional responses of Δ9-tetrahydrocannabinol. Although progress has been made in understanding cannabinoid binding and receptor activation, detailed knowledge of the dynamics involved in the activation mechanism of CB1 is lacking. Here, we use recently determined CB1 crystal structures to analyze its transition from inactive to active state by performing unbiased microsecond-length molecular dynamics (MD) simulations, totaling 32 µs, with and without bound potent cannabinoid agonist CP-55940. CB1 activation is characterized by an upward axial movement of transmembrane (TM) helix 3, inward movement of TM7, and outward movement of TM6. These conformational changes collectively allow Gi protein docking, although fully active states of the receptor occur only transiently during MD simulations. Additionally, positive allosteric modulation of CB1 by anionic phospholipids is found to increase action of the bound agonist. Specifically, this involves protein-lipid interactions at intracellular loop 3, TM6, and ionic lock residue Arg2143.50.