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.

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.

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.

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.

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.

Distinct Dopamine D2 Receptor Antagonists Differentially Impact D2 Receptor Oligomerization.

Dopamine D2 receptors (D2R) are known to form transient homodimer complexes, of which the increased formation has already been associated with development of schizophrenia. Pharmacological targeting and modulation of the equilibrium of these receptor homodimers might lead to a better understanding of the critical role played by these complexes in physiological and pathological conditions. Whereas agonist addition has shown to prolong the D2R dimer lifetime and increase the level of dimer formation, the possible influence of D2R antagonists on dimerization has remained rather unexplored. Here, using a live-cell reporter assay based on the functional complementation of a split Nanoluciferase, a panel of six D2R antagonists were screened for their ability to modulate the level of D2LR dimer formation. Incubation with the D2R antagonist spiperone decreased the level of D2LR dimer formation significantly by 40-60% in real-time and after long-term (≥16 h) incubations. The fact that dimer formation of the well-studied A2a-D2LR dimer was not altered following incubation with spiperone supports the specificity of this observation. Other D2R antagonists, such as clozapine, risperidone, and droperidol did not significantly evoke this dissociation event. Furthermore, molecular modeling reveals that spiperone presents specific Tyr1995.48 and Phe3906.52 conformations, compared to clozapine, which may determine D2R homodimerization.

Representation Learning for Class C G Protein-Coupled Receptors Classification.

G protein-coupled receptors (GPCRs) are integral cell membrane proteins of relevance for pharmacology. The complete tertiary structure including both extracellular and transmembrane domains has not been determined for any member of class C GPCRs. An alternative way to work on GPCR structural models is the investigation of their functionality through the analysis of their primary structure. For this, sequence representation is a key factor for the GPCRs' classification context, where usually, feature engineering is carried out. In this paper, we propose the use of representation learning to acquire the features that best represent the class C GPCR sequences and at the same time to obtain a model for classification automatically. Deep learning methods in conjunction with amino acid physicochemical property indices are then used for this purpose. Experimental results assessed by the classification accuracy, Matthews' correlation coefficient and the balanced error rate show that using a hydrophobicity index and a restricted Boltzmann machine (RBM) can achieve performance results (accuracy of 92.9%) similar to those reported in the literature. As a second proposal, we combine two or more physicochemical property indices instead of only one as the input for a deep architecture in order to add information from the sequences. Experimental results show that using three hydrophobicity-related index combinations helps to improve the classification performance (accuracy of 94.1%) of an RBM better than those reported in the literature for class C GPCRs without using feature selection methods.

Paternal Age and Numerical Chromosome Abnormalities in Human Spermatozoa.

This study explores the relationship between numerical chromosome abnormalities in sperm and age in healthy men. We performed FISH in the spermatozoa of 10 donors from the general population: 5 men younger than 40 years of age and 5 fertile men older than 60 years of age. For each chromosome, 1,000 sperm nuclei were analyzed, with a total of 15,000 sperm nuclei for each donor. We used a single sperm sample per donor, thus minimizing intra-donor variability and optimizing consistent analysis. FISH with a TelVysion assay, which provides data on aneuploidy of 19 chromosomes, was used in order to gain a more genome-wide perspective of the level of aneuploidy. Aneuploidy and diploidy rates observed in the younger and older groups were compared. There were no significant differences in the incidence of autosomal disomy, sex chromosome disomy, total chromosome disomy, diploidy, nor total numerical abnormalities between younger and older men. This work confirms that aneuploidy of the sex chromosomes is more common than that of autosomes and that this does not change with age. Our results suggest that some probe combinations have a tendency to indicate higher levels of diploidy, thus potentially affecting FISH results and highlighting the limitations of FISH.

An allosteric modulator to control endogenous G protein-coupled receptors with light.

Controlling drug activity with light offers the possibility of enhancing pharmacological selectivity with spatial and temporal regulation, thus enabling highly localized therapeutic effects and precise dosing patterns. Here we report on the development and characterization of what is to our knowledge the first photoswitchable allosteric modulator of a G protein-coupled receptor. Alloswitch-1 is selective for the metabotropic glutamate receptor mGlu5 and enables the optical control of endogenous mGlu5 receptors.

Overlapping binding sites drive allosteric agonism and positive cooperativity in type 4 metabotropic glutamate receptors.

Type 4 metabotropic glutamate (mGlu4) receptors are emerging targets for the treatment of various disorders. Accordingly, numerous mGlu4-positive allosteric modulators (PAMs) have been identified, some of which also display agonist activity. To identify the structural bases for their allosteric action, we explored the relationship between the binding pockets of mGlu4 PAMs with different chemical scaffolds and their functional properties. By use of innovative mGlu4 biosensors and second-messenger assays, we show that all PAMs enhance agonist action on the receptor through different degrees of allosteric agonism and positive cooperativity. For example, whereas VU0155041 and VU0415374 display equivalent efficacies [log(τ(B)) = 1.15 ± 0.38 and 1.25 ± 0.44, respectively], they increase the ability of L-AP4 to stabilize the active conformation of the receptor by 4 and 39 times, respectively. Modeling and docking studies identify 2 overlapping binding pockets as follows: a first site homologous to the pocket of natural agonists of class A GPCRs linked to allosteric agonism and a second one pointing toward a site topographically homologous to the Na(+) binding pocket of class A GPCRs, occupied by PAMs exhibiting the strongest cooperativity. These results reveal that intrinsic efficacy and cooperativity of mGlu4 PAMs are correlated with their binding mode, and vice versa, integrating structural and functional knowledge from different GPCR classes.

Quantifying conformational changes in GPCRs: glimpse of a common functional mechanism.

BACKGROUND: G-protein-coupled receptors (GPCRs) are important drug targets and a better understanding of their molecular mechanisms would be desirable. The crystallization rate of GPCRs has accelerated in recent years as techniques have become more sophisticated, particularly with respect to Class A GPCRs interacting with G-proteins. These developments have made it possible for a quantitative analysis of GPCR geometrical features and binding-site conformations, including a statistical comparison between Class A GPCRs in active (agonist-bound) and inactive (antagonist-bound) states. RESULTS: Here we implement algorithms for the analysis of interhelical angles, distances, interactions and binding-site volumes in the transmembrane domains of 25 Class A GPCRs (7 active and 18 inactive). Two interhelical angles change in a statistically significant way between average inactive and active states: TM3-TM6 (by -9°) and TM6-TM7 (by +12°). A third interhelical angle: TM5-TM6 shows a trend, changing by -9°. In the transition from inactive to active states, average van der Waals interactions between TM3 and TM7 significantly increase as the average distance between them decreases by >2 Å. Average H-bonding between TM3 and TM6 decreases but is seemingly compensated by an increase in H-bonding between TM5 and TM6. In five Class A GPCRs, crystallized in both active and inactive states, increased H-bonding of agonists to TM6 and TM7, relative to antagonists, is observed. These protein-agonist interactions likely favour a change in the TM6-TM7 angle, which creates a narrowing in the binding pocket of activated receptors and an average ~200 Å(3) reduction in volume. CONCLUSIONS: In terms of similar conformational changes and agonist binding pattern, Class A GPCRs appear to share a common mechanism of activation, which can be exploited in future drug development.

Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors.

BACKGROUND: The characterization of proteins in families and subfamilies, at different levels, entails the definition and use of class labels. When the adscription of a protein to a family is uncertain, or even wrong, this becomes an instance of what has come to be known as a label noise problem. Label noise has a potentially negative effect on any quantitative analysis of proteins that depends on label information. This study investigates class C of G protein-coupled receptors, which are cell membrane proteins of relevance both to biology in general and pharmacology in particular. Their supervised classification into different known subtypes, based on primary sequence data, is hampered by label noise. The latter may stem from a combination of expert knowledge limitations and the lack of a clear correspondence between labels that mostly reflect GPCR functionality and the different representations of the protein primary sequences. RESULTS: In this study, we describe a systematic approach, using Support Vector Machine classifiers, to the analysis of G protein-coupled receptor misclassifications. As a proof of concept, this approach is used to assist the discovery of labeling quality problems in a curated, publicly accessible database of this type of proteins. We also investigate the extent to which physico-chemical transformations of the protein sequences reflect G protein-coupled receptor subtype labeling. The candidate mislabeled cases detected with this approach are externally validated with phylogenetic trees and against further trusted sources such as the National Center for Biotechnology Information, Universal Protein Resource, European Bioinformatics Institute and Ensembl Genome Browser information repositories. CONCLUSIONS: In quantitative classification problems, class labels are often by default assumed to be correct. Label noise, though, is bound to be a pervasive problem in bioinformatics, where labels may be obtained indirectly through complex, many-step similarity modelling processes. In the case of G protein-coupled receptors, methods capable of singling out and characterizing those sequences with consistent misclassification behaviour are required to minimize this problem. A systematic, Support Vector Machine-based method has been proposed in this study for such purpose. The proposed method enables a filtering approach to the label noise problem and might become a support tool for database curators in proteomics.

Helix 3 acts as a conformational hinge in Class A GPCR activation: An analysis of interhelical interaction energies in crystal structures.

A collection of crystal structures of rhodopsin, ß2-adrenergic and adenosine A2A receptors in active, intermediate and inactive states were selected for structural and energetic analyses to identify the changes involved in the activation/deactivation of Class A GPCRs. A set of helix interactions exclusive to either inactive or active/intermediate states were identified. The analysis of these interactions distinguished some local conformational changes involved in receptor activation, in particular, a packing between the intracellular domains of transmembrane helices H3 and H7 and a separation between those of H2 and H6. Also, differential movements of the extracellular and intracellular domains of these helices are apparent. Moreover, a segment of residues in helix H3, including residues L/I3.40 to L3.43, is identified as a key component of the activation mechanism, acting as a conformational hinge between extracellular and intracellular regions. Remarkably, the influence on the activation process of some glutamic and aspartic acidic residues and, as a consequence, the influence of variations on local pH is highlighted. Structural hypotheses that arose from the analysis of rhodopsin, ß2-adrenergic and adenosine A2A receptors were tested on the active and inactive M2 muscarinic acetylcholine receptor structures and further discussed in the context of the new mechanistic insights provided by the recently determined active and inactive crystal structures of the µ-opioid receptor. Overall, the structural and energetic analyses of the interhelical interactions present in this collection of Class A GPCRs suggests the existence of a common general activation mechanism featuring a chemical space useful for drug discovery exploration.

Computational analysis of negative and positive allosteric modulator binding and function in metabotropic glutamate receptor 5 (in)activation.

Metabotropic glutamate receptors (mGluRs) are high-profile G-protein coupled receptors drug targets because of their involvement in several neurological disease states, and mGluR5 in particular is a subtype whose controlled allosteric modulation, both positive and negative, can potentially be useful for the treatment of schizophrenia and relief of chronic pain, respectively. Here we model mGluR5 with a collection of positive and negative allosteric modulators (PAMs and NAMs) in both active and inactive receptor states, in a manner that is consistent with experimental information, using a specialized protocol that includes homology to increase docking accuracy, and receptor relaxation to generate an individual induced fit with each allosteric modulator. Results implicate two residues in particular for NAM and PAM function: NAM interaction with W785 for receptor inactivation, and NAM/PAM H-bonding with S809 for receptor (in)activation. Models suggest the orientation of the H-bond between allosteric modulator and S809, controlled by PAM/NAM chemistry, influences the position of TM7, which in turn influences the shape of the allosteric site, and potentially the receptor state. NAM-bound and PAM-bound mGluR5 models also reveal that although PAMs and NAMs bind in the same pocket and share similar binding modes, they have distinct effects on the conformation of the receptor. Our models, together with the identification of a possible activation mechanism, may be useful in the rational design of new allosteric modulators for mGluR5.

Mathematical modeling of G protein-coupled receptor function: what can we learn from empirical and mechanistic models?

Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists.

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.

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.

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.

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.

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.