Cardiac Corrected QT Interval Changes Among Patients Treated for COVID-19 Infection During the Early Phase of the Pandemic.

Importance: Critical illness, a marked inflammatory response, and viruses such as SARS-CoV-2 may prolong corrected QT interval (QTc). Objective: To evaluate baseline QTc interval on 12-lead electrocardiograms (ECGs) and ensuing changes among patients with and without COVID-19. Design, Setting, and Participants: This cohort study included 3050 patients aged 18 years and older who underwent SARS-CoV-2 testing and had ECGs at Columbia University Irving Medical Center from March 1 through May 1, 2020. Patients were analyzed by treatment group over 5 days, as follows: hydroxychloroquine with azithromycin, hydroxychloroquine alone, azithromycin alone, and neither hydroxychloroquine nor azithromycin. ECGs were manually analyzed by electrophysiologists masked to COVID-19 status. Multivariable modeling evaluated clinical associations with QTc prolongation from baseline. Exposures: COVID-19, hydroxychloroquine, azithromycin. Main Outcomes and Measures: Mean QTc prolongation, percentage of patients with QTc of 500 milliseconds or greater. Results: A total of 965 patients had more than 2 ECGs and were included in the study, with 561 (58.1%) men, 198 (26.2%) Black patients, and 191 (19.8%) aged 80 years and older. There were 733 patients (76.0%) with COVID-19 and 232 patients (24.0%) without COVID-19. COVID-19 infection was associated with significant mean QTc prolongation from baseline by both 5-day and 2-day multivariable models (5-day, patients with COVID-19: 20.81 [95% CI, 15.29 to 26.33] milliseconds; P < .001; patients without COVID-19: -2.01 [95% CI, -17.31 to 21.32] milliseconds; P = .93; 2-day, patients with COVID-19: 17.40 [95% CI, 12.65 to 22.16] milliseconds; P < .001; patients without COVID-19: 0.11 [95% CI, -12.60 to 12.81] milliseconds; P = .99). COVID-19 infection was independently associated with a modeled mean 27.32 (95% CI, 4.63-43.21) millisecond increase in QTc at 5 days compared with COVID-19-negative status (mean QTc, with COVID-19: 450.45 [95% CI, 441.6 to 459.3] milliseconds; without COVID-19: 423.13 [95% CI, 403.25 to 443.01] milliseconds; P = .01). More patients with COVID-19 not receiving hydroxychloroquine and azithromycin had QTc of 500 milliseconds or greater compared with patients without COVID-19 (34 of 136 [25.0%] vs 17 of 158 [10.8%], P = .002). Multivariable analysis revealed that age 80 years and older compared with those younger than 50 years (mean difference in QTc, 11.91 [SE, 4.69; 95% CI, 2.73 to 21.09]; P = .01), severe chronic kidney disease compared with no chronic kidney disease (mean difference in QTc, 12.20 [SE, 5.26; 95% CI, 1.89 to 22.51; P = .02]), elevated high-sensitivity troponin levels (mean difference in QTc, 5.05 [SE, 1.19; 95% CI, 2.72 to 7.38]; P < .001), and elevated lactate dehydrogenase levels (mean difference in QTc, 5.31 [SE, 2.68; 95% CI, 0.06 to 10.57]; P = .04) were associated with QTc prolongation. Torsades de pointes occurred in 1 patient (0.1%) with COVID-19. Conclusions and Relevance: In this cohort study, COVID-19 infection was independently associated with significant mean QTc prolongation at days 5 and 2 of hospitalization compared with day 0. More patients with COVID-19 had QTc of 500 milliseconds or greater compared with patients without COVID-19.

Frequency of Atrial Arrhythmia in Hospitalized Patients With COVID-19.

There is growing evidence that COVID-19 can cause cardiovascular complications. However, there are limited data on the characteristics and importance of atrial arrhythmia (AA) in patients hospitalized with COVID-19. Data from 1,029 patients diagnosed with of COVID-19 and admitted to Columbia University Medical Center between March 1, 2020 and April 15, 2020 were analyzed. The diagnosis of AA was confirmed by 12 lead electrocardiographic recordings, 24-hour telemetry recordings and implantable device interrogations. Patients' history, biomarkers and hospital course were reviewed. Outcomes that were assessed were intubation, discharge and mortality. Of 1,029 patients reviewed, 82 (8%) were diagnosed with AA in whom 46 (56%) were new-onset AA 16 (20%) recurrent paroxysmal and 20 (24%) were chronic persistent AA. Sixty-five percent of the patients diagnosed with AA (n=53) died. Patients diagnosed with AA had significantly higher mortality compared with those without AA (65% vs 21%; p < 0.001). Predictors of mortality were older age (Odds Ratio (OR)=1.12, [95% Confidence Interval (CI), 1.04 to 1.22]); male gender (OR=6.4 [95% CI, 1.3 to 32]); azithromycin use (OR=13.4 [95% CI, 2.14 to 84]); and higher D-dimer levels (OR=2.8 [95% CI, 1.1 to 7.3]). In conclusion, patients diagnosed with AA had 3.1 times significant increase in mortality rate versus patients without diagnosis of AA in COVID-19 patients. Older age, male gender, azithromycin use and higher baseline D-dimer levels were predictors of mortality.

Admission Cardiac Diagnostic Testing with Electrocardiography and Troponin Measurement Prognosticates Increased 30-Day Mortality in COVID-19.

Background Cardiovascular involvement in coronavirus disease 2019 (COVID-19) is common and leads to worsened mortality. Diagnostic cardiovascular studies may be helpful for resource appropriation and identifying patients at increased risk for death. Methods and Results We analyzed 887 patients (aged 64±17 years) admitted with COVID-19 from March 1 to April 3, 2020 in New York City with 12 lead electrocardiography within 2 days of diagnosis. Demographics, comorbidities, and laboratory testing, including high sensitivity cardiac troponin T (hs-cTnT), were abstracted. At 30 days follow-up, 556 patients (63%) were living without requiring mechanical ventilation, 123 (14%) were living and required mechanical ventilation, and 203 (23%) had expired. Electrocardiography findings included atrial fibrillation or atrial flutter (AF/AFL) in 46 (5%) and ST-T wave changes in 306 (38%). 27 (59%) patients with AF/AFL expired as compared to 181 (21%) of 841 with other non-life-threatening rhythms (P<0.001). Multivariable analysis incorporating age, comorbidities, AF/AFL, QRS abnormalities, and ST-T wave changes, and initial hs-cTnT ≥20 ng/L showed that increased age (HR 1.04/year), elevated hs-cTnT (HR 4.57), AF/AFL (HR 2.07), and a history of coronary artery disease (HR 1.56) and active cancer (HR 1.87) were associated with increased mortality. Conclusions Myocardial injury with hs-cTnT ≥20 ng/L, in addition to cardiac conduction perturbations, especially AF/AFL, upon hospital admission for COVID-19 infection is associated with markedly increased risk for mortality than either diagnostic abnormality alone.

Clinical and cardiac characteristics of COVID-19 mortalities in a diverse New York City Cohort.

INTRODUCTION: Electrocardiographic characteristics in COVID-19-related mortality have not yet been reported, particularly in racial/ethnic minorities. METHODS AND RESULTS: We reviewed demographics, laboratory and cardiac tests, medications, and cardiac rhythm proximate to death or initiation of comfort care for patients hospitalized with a positive SARS-CoV-2 reverse-transcriptase polymerase chain reaction in three New York City hospitals between March 1 and April 3, 2020 who died. We described clinical characteristics and compared factors contributing toward arrhythmic versus nonarrhythmic death. Of 1258 patients screened, 133 died and were enrolled. Of these, 55.6% (74/133) were male, 69.9% (93/133) were racial/ethnic minorities, and 88.0% (117/133) had cardiovascular disease. The last cardiac rhythm recorded was VT or fibrillation in 5.3% (7/133), pulseless electrical activity in 7.5% (10/133), unspecified bradycardia in 0.8% (1/133), and asystole in 26.3% (35/133). Most 74.4% (99/133) died receiving comfort measures only. The most common abnormalities on admission electrocardiogram included abnormal QRS axis (25.8%), atrial fibrillation/flutter (14.3%), atrial ectopy (12.0%), and right bundle branch block (11.9%). During hospitalization, an additional 17.6% developed atrial ectopy, 14.7% ventricular ectopy, 10.1% atrial fibrillation/flutter, and 7.8% a right ventricular abnormality. Arrhythmic death was confirmed or suspected in 8.3% (11/133) associated with age, coronary artery disease, asthma, vasopressor use, longer admission corrected QT interval, and left bundle branch block (LBBB). CONCLUSIONS: Conduction, rhythm, and electrocardiographic abnormalities were common during COVID-19-related hospitalization. Arrhythmic death was associated with age, coronary artery disease, asthma, longer admission corrected QT interval, LBBB, ventricular ectopy, and usage of vasopressors. Most died receiving comfort measures.

The Prognostic Value of Electrocardiogram at Presentation to Emergency Department in Patients With COVID-19.

OBJECTIVE: To study whether combining vital signs and electrocardiogram (ECG) analysis can improve early prognostication. METHODS: This study analyzed 1258 adults with coronavirus disease 2019 who were seen at three hospitals in New York in March and April 2020. Electrocardiograms at presentation to the emergency department were systematically read by electrophysiologists. The primary outcome was a composite of mechanical ventilation or death 48 hours from diagnosis. The prognostic value of ECG abnormalities was assessed in a model adjusted for demographics, comorbidities, and vital signs. RESULTS: At 48 hours, 73 of 1258 patients (5.8%) had died and 174 of 1258 (13.8%) were alive but receiving mechanical ventilation with 277 of 1258 (22.0%) patients dying by 30 days. Early development of respiratory failure was common, with 53% of all intubations occurring within 48 hours of presentation. In a multivariable logistic regression, atrial fibrillation/flutter (odds ratio [OR], 2.5; 95% CI, 1.1 to 6.2), right ventricular strain (OR, 2.7; 95% CI, 1.3 to 6.1), and ST segment abnormalities (OR, 2.4; 95% CI, 1.5 to 3.8) were associated with death or mechanical ventilation at 48 hours. In 108 patients without these ECG abnormalities and with normal respiratory vitals (rate <20 breaths/min and saturation >95%), only 5 (4.6%) died or required mechanical ventilation by 48 hours versus 68 of 216 patients (31.5%) having both ECG and respiratory vital sign abnormalities. CONCLUSION: The combination of abnormal respiratory vital signs and ECG findings of atrial fibrillation/flutter, right ventricular strain, or ST segment abnormalities accurately prognosticates early deterioration in patients with coronavirus disease 2019 and may assist with patient triage.

Comparison of Pharmacological Properties between the Kappa Opioid Receptor Agonist Nalfurafine and 42B, Its 3-Dehydroxy Analogue: Disconnect between in Vitro Agonist Bias and in Vivo Pharmacological Effects.

Nalfurafine, a moderately selective kappa opioid receptor (KOR) agonist, is used in Japan for treatment of itch without causing dysphoria or psychotomimesis. Here we characterized the pharmacology of compound 42B, a 3-dehydroxy analogue of nalfurafine and compared with that of nalfurafine. Nalfurafine and 42B acted as full KOR agonists and partial µ opioid receptor (MOR) agonists, but 42B showed much lower potency for both receptors and lower KOR/MOR selectivity, different from previous reports. Molecular modeling revealed that water-mediated hydrogen-bond formation between 3-OH of nalfurafine and KOR accounted for its higher KOR potency than 42B. The higher potency of both at KOR over MOR may be due to hydrogen-bond formation between nonconserved Y7.35 of KOR and their carbonyl groups. Both showed modest G protein signaling biases. In mice, like nalfurafine, 42B produced antinociceptive and antiscratch effects and did not cause conditioned place aversion (CPA) in the effective dose ranges. Unlike nalfurafine, 42B caused motor incoordination and hypolocomotion. As both agonists showed G protein biases, yet produced different effects on locomotor activity and motor incoordination, the findings and those in the literature suggest caution in correlating in vitro biochemical data with in vivo behavior effects. The factors contributing to the disconnect, including pharmacodynamic and pharmacokinetic issues, are discussed. In addition, our results suggest that among the KOR-induced adverse behaviors, CPA can be separated from motor incoordination and hypolocomotion.

Cardiac electrophysiology consultative experience at the epicenter of the COVID-19 pandemic in the United States.

BACKGROUND: The COVID-19 pandemic has greatly altered the practice of cardiac electrophysiology around the world for the foreseeable future. Professional organizations have provided guidance for practitioners, but real-world examples of the consults and responsibilities cardiac electrophysiologists face during a surge of COVID-19 patients is lacking. METHODS: In this observational case series we report on 29 consecutive inpatient electrophysiology consultations at a major academic medical center in New York City, the epicenter of the pandemic in the United States, during a 2 week period from March 30-April 12, 2020, when 80% of hospital beds were occupied by COVID-19 patients, and the New York City metropolitan area accounted for 10% of COVID-19 cases worldwide. RESULTS: Reasons for consultation included: Atrial tachyarrhythmia (31%), cardiac implantable electronic device management (28%), bradycardia (14%), QTc prolongation (10%), ventricular arrhythmia (7%), post-transcatheter aortic valve replacement conduction abnormality (3.5%), ventricular pre-excitation (3.5%), and paroxysmal supraventricular tachycardia (3.5%). Twenty-four patients (86%) were positive for COVID-19 by nasopharyngeal swab. All elective procedures were canceled, and only one urgent device implantation was performed. Thirteen patients (45%) required in-person evaluation and the remainder were managed remotely. CONCLUSION: Our experience shows that the application of a massive alteration in workflow and personnel forced by the pandemic allowed our team to efficiently address the intersection of COVID-19 with a range of electrophysiology issues. This experience will prove useful as guidance for emerging hot spots or areas affected by future waves of the pandemic.

Performance of electrophysiology procedures at an academic medical center amidst the 2020 coronavirus (COVID-19) pandemic.

A global coronavirus (COVID-19) pandemic occurred at the start of 2020 and is already responsible for more than 74 000 deaths worldwide, just over 100 years after the influenza pandemic of 1918. At the center of the crisis is the highly infectious and deadly SARS-CoV-2, which has altered everything from individual daily lives to the global economy and our collective consciousness. Aside from the pulmonary manifestations of disease, there are likely to be several electrophysiologic (EP) sequelae of COVID-19 infection and its treatment, due to consequences of myocarditis and the use of QT-prolonging drugs. Most crucially, the surge in COVID-19 positive patients that have already overwhelmed the New York City hospital system requires conservation of hospital resources including personal protective equipment (PPE), reassignment of personnel, and reorganization of institutions, including the EP laboratory. In this proposal, we detail the specific protocol changes that our EP department has adopted during the COVID-19 pandemic, including performance of only urgent/emergent procedures, after hours/7-day per week laboratory operation, single attending-only cases to preserve PPE, appropriate use of PPE, telemedicine and video chat follow-up appointments, and daily conferences to collectively manage the clinical and ethical dilemmas to come. We discuss also discuss how we perform EP procedures on presumed COVID positive and COVID tested positive patients to highlight issues that others in the EP community may soon face in their own institution as the virus continues to spread nationally and internationally.

Restructuring Electrophysiology During the COVID-19 Pandemic: A Practical Guide From a New York City Hospital Network.

The coronavirus disease 2019 crisis is a global pandemic of a novel infectious disease with far-ranging public health implications. With regard to cardiac electrophysiology (EP) services, we discuss the "real-world" challenges and solutions that have been essential for efficient and successful (1) ramping down of standard clinical practice patterns and (2) pivoting of workflow processes to meet the demands of this pandemic. The aims of these recommendations are to outline: (1) essential practical steps to approaching procedures, as well as outpatient and inpatient care of EP patients, with relevant examples, (2) successful strategies to minimize exposure risk to patients and clinical staff while also balancing resource utilization, (3) challenges related to redeployment and restructuring of clinical and support staff, and (4) considerations regarding continued collaboration with clinical and administrative colleagues to implement these changes. While process changes will vary across practices and hospital systems, we believe that these experiences from 4 different EP sections in a large New York City hospital network currently based in the global epicenter of the coronavirus disease 2019 pandemic will prove useful for other EP practices adapting their own practices in preparation for local surges.

Quantitating Ligand Bias Using the Competitive Model of Ligand Activity.

G protein-coupled receptors (GPCRs) can interact with both G proteins and ß-arrestin proteins to propagate different signaling outputs. In some contexts, agonists may drive the receptor to preferentially engage one of these effectors over the other. Such "ligand bias" may present a means to impart pathway-selective signaling downstream of this class of receptors. In cases where physiological responses are mediated by diverse pathways, this could, in part, provide a means to refine GPCR therapeutics. Cell-based signaling assays are used to measure the potential for signaling bias in vitro, and these measures take into account potency, efficacy, and the overall capacity of the assay. However, narrow assay windows sometimes limit the confidence in estimating agonist activity, if a compound performs as a very weakly efficacious partial agonist. This lack of response in an assay hampers the ability to measure and compare potencies, and the degree of separation of an agonist's performance, between two assays. In this chapter, we describe in detail a method for the estimation of the relative activity of a partial agonist and provide a stepwise protocol for calculating bias when this case arises.

Analysis of Biased Agonism.

Agonists and most natural ligands bind to receptors in their inactive state and quickly induce an active receptor conformation that initiates cell signaling. The active receptor state initiates signaling because of its structural complementariness with coupling proteins that activate signaling pathways, such as G proteins and G protein-coupled receptor kinases. Agonist bias refers to the propensity of an agonist to direct receptor signaling through one pathway relative to another. Thus, if the agonist exhibits much higher affinity for active state 1 compared to active state 2, it will cause a robust activation of receptor coupling protein 1 but not 2, and ultimately, a preferential stimulation of signaling pathway 1. Biased agonists are potentially more selective therapeutic agents because there are numerous cases where the therapeutic and adverse effects of an agonist are mediated by distinct pathways involving G proteins and ß-arrestin. Given the mechanism for agonist bias, the most straightforward approach for quantifying bias involves the estimation of agonist affinity for the inactive receptor state and the active receptor states involved in signaling through different pathways. The approach provides quantitative estimates of the sensitivities of different signaling pathways, enabling one to determine to what extent the observed selectivity is caused by agonist or system bias. In addition, the approach is a powerful adjunct to in silico docking studies and can be applied to in vivo assays, structure-activity relationships, and the analysis of published agonist concentration-response curves.

PDE8 Is Expressed in Human Airway Smooth Muscle and Selectively Regulates cAMP Signaling by ß2-Adrenergic Receptors and Adenylyl Cyclase 6.

Two cAMP signaling compartments centered on adenylyl cyclase (AC) exist in human airway smooth muscle (HASM) cells, one containing ß2-adrenergic receptor AC6 and another containing E prostanoid receptor AC2. We hypothesized that different PDE isozymes selectively regulate cAMP signaling in each compartment. According to RNA-sequencing data, 18 of 24 PDE genes were expressed in primary HASM cells derived from age- and sex-matched donors with and without asthma. PDE8A was the third most abundant of the cAMP-degrading PDE genes, after PDE4A and PDE1A. Knockdown of PDE8A using shRNA evoked twofold greater cAMP responses to 1 µM forskolin in the presence of 3-isobutyl-1-methylxanthine. Overexpression of AC2 did not alter this response, but overexpression of AC6 increased cAMP responses an additional 80%. We examined cAMP dynamics in live HASM cells using a fluorescence sensor. PF-04957325, a PDE8-selective inhibitor, increased basal cAMP concentrations by itself, indicating a significant basal level of cAMP synthesis. In the presence of an AC inhibitor to reduce basal signaling, PF-04957325 accelerated cAMP production and increased the inhibition of cell proliferation induced by isoproterenol, but it had no effect on cAMP concentrations or cell proliferation regulated by prostaglandin E2. Lipid raft fractionation of HASM cells revealed PDE8A immunoreactivity in buoyant fractions containing caveolin-1 and AC5/6 immunoreactivity. Thus, PDE8 is expressed in lipid rafts of HASM cells, where it specifically regulates ß2-adrenergic receptor AC6 signaling without effects on signaling by the E prostanoid receptors 2/4-AC2 complex. In airway diseases such as asthma and chronic obstructive pulmonary disease, PDE8 may represent a novel therapeutic target to modulate HASM responsiveness and airway remodeling.

Estimation of the receptor-state affinity constants of ligands in functional studies using wild type and constitutively active mutant receptors: Implications for estimation of agonist bias.

We describe a method for estimating the affinities of ligands for active and inactive states of a G protein-coupled receptor (GPCR). Our protocol involves measuring agonist-induced signaling responses of a wild type GPCR and a constitutively active mutant of it under control conditions and after partial receptor inactivation or reduced receptor expression. Our subsequent analysis is based on the assumption that the activating mutation increases receptor isomerization into the active state without affecting the affinities of ligands for receptor states. A means of confirming this assumption is provided. Global nonlinear regression analysis yields estimates of 1) the active (Kact) and inactive (Kinact) receptor-state affinity constants, 2) the isomerization constant of the unoccupied receptor (Kq-obs), and 3) the sensitivity constant of the signaling pathway (KE-obs). The latter two parameters define the output response of the receptor, and hence, their ratio (Kq-obs/KE) is a useful measure of system bias. If the cellular system is reasonably stable and the Kq-obs and KE-obs values of the signaling pathway are known, the Kact and Kinact values of additional agonists can be estimated in subsequent experiments on cells expressing the wild type receptor. We validated our method through computer simulation, an analytical proof, and analysis of previously published data. Our approach provides 1) a more meaningful analysis of structure-activity relationships, 2) a means of validating in silico docking experiments on active and inactive receptor structures and 3) an absolute, in contrast to relative, measure of agonist bias.

Cooperativity Has Empirical and Ultimate Levels of Explanation.

Controversy over the meaning of pharmacological parameters often arises because of a lack of appreciation of different hierarchical levels of analysis. In a recent letter in Trends in Pharmacological Sciences, Zhang and Kavana [1] concluded that my two-state model for allosterism lacks cooperativity, even though Figures 5 and 6 in my review [2] illustrate examples of how the two-state model yields specific cooperativity values. Here, I explain how the two-state model (receptor-state analysis) gives rise to the cooperativity parameter (α) of the allosteric ternary complex model (receptor-population analysis).

Functional studies cast light on receptor states.

Contemporary analysis of the functional responses of G-protein-coupled receptors (GPCRs) usually addresses drug-receptor interactions from the perspective of the average behavior of the receptor population. This behavior is characterized in terms of observed affinity and efficacy. Efficacy is a measure of how well a drug activates the receptor population and observed affinity a measure of how potently a drug occupies the receptor population. The latter is quantified in terms of the dissociation constant of the ligand-receptor complex. At a deeper level of analysis, drug-receptor interactions are described in terms of ligand affinity constants for active and inactive receptor states. Unlike observed affinity and efficacy, estimates of receptor state affinity constants are unperturbed by G proteins, guanine nucleotides, or other signaling proteins that interact with the receptor. Recent advances in the analysis of the functional responses of GPCRs have enabled the estimation of receptor state affinity constants. These constants provide a more fundamental measure of drug-receptor interactions and are useful in analyzing structure-activity relationships and in quantifying allosterism, biased signaling, and receptor-subtype selectivity.

Intrinsic relative activities of κ opioid agonists in activating Gα proteins and internalizing receptor: Differences between human and mouse receptors.

Several investigators recently identified biased κ opioid receptor (KOP receptor) agonists. However, no comprehensive study of the functional selectivity of available KOP receptor agonists at the human and mouse KOP receptors (hKOP receptor and mKOP receptor, respectively) has been published. Here we examined the ability of over 20 KOP receptor agonists to activate G proteins and to internalize the receptor. Clonal neuro-2a mouse neuroblastoma (N2a) cells stably transfected with the hKOP receptor or mKOP receptor were used. We employed agonist-induced [(35)S]GTPγS binding and KOP receptor internalization as measures of activation of G protein and ß-arrestin pathways, respectively. The method of Ehlert and colleagues was used to quantify intrinsic relative activities at G protein activation (RAi-G) and receptor internalization (RAi-I) and the degree of functional selectivity between the two [Log RAi-G - logRAi-I, RAi-G/RAi-I and bias factor]. The parameter, RAi, represents a relative estimate of agonist affinity for the active receptor state that elicits a given response. The endogenous ligand dynorphin A (1-17) was designated as the balanced ligand with a bias factor of 1. Interestingly, we found that there were species differences in functional selectivity. The most striking differences were for 12-epi-salvinorin A, U69,593, and ICI-199,441. 12-Epi-salvinorin A was highly internalization-biased at the mKOP receptor, but apparently G protein-biased at hKOP receptor. U69,593 was much more internalization-biased at mKOP receptor than hKOP receptor. ICI199,441 showed internalization-biased at the mKOP receptor and G protein-biased at the hKOP receptor. Possible mechanisms for the observed species differences are discussed.

A novel method for analyzing extremely biased agonism at G protein-coupled receptors.

Seven transmembrane receptors were originally named and characterized based on their ability to couple to heterotrimeric G proteins. The assortment of coupling partners for G protein-coupled receptors has subsequently expanded to include other effectors (most notably the ßarrestins). This diversity of partners available to the receptor has prompted the pursuit of ligands that selectively activate only a subset of the available partners. A biased or functionally selective ligand may be able to distinguish between different active states of the receptor, and this would result in the preferential activation of one signaling cascade more than another. Although application of the "standard" operational model for analyzing ligand bias is useful and suitable in most cases, there are limitations that arise when the biased agonist fails to induce a significant response in one of the assays being compared. In this article, we describe a quantitative method for measuring ligand bias that is particularly useful for such cases of extreme bias. Using simulations and experimental evidence from several κ opioid receptor agonists, we illustrate a "competitive" model for quantitating the degree and direction of bias. By comparing the results obtained from the competitive model with the standard model, we demonstrate that the competitive model expands the potential for evaluating the bias of very partial agonists. We conclude the competitive model provides a useful mechanism for analyzing the bias of partial agonists that exhibit extreme bias.

A kinetic model of GPCRs: analysis of G protein activity, occupancy, coupling and receptor-state affinity constants.

CONTEXT: G protein-coupled receptors are vital macromolecules for a wide variety of physiological processes. Upon agonist binding, these receptors accelerate the exchange of GDP for GTP in G proteins coupled to them. The activated G protein interacts with effector proteins to implement downstream biological functions. OBJECTIVE: We present a kinetic, quaternary complex model, based on a system of coupled linear first-order differential equations, which accounts for the binding attributes of the ligand, receptor, G protein and two types of guanine nucleotide (GDP and GTP) as well as for GTPase activity. METHODS: We solved the model numerically to predict the extents of G protein activation, receptor occupancy by ligand and receptor coupling that result from varying the ligand concentration, presence of GDP and/or GTP, the ratio of G protein to receptor and the equilibrium constants governing receptor pre-coupling and constitutive activity. We also simulated responses downstream from G protein activation using a transducer function. RESULTS: Our model shows that agonist-induced G protein activation can occur with either a net decrease or increase in total receptor-G protein coupling. In addition, we demonstrate that affinity constants of the ligand for both the active and inactive states of the receptor can be derived to a close approximation from analysis of simulated responses downstream from receptor activation. DISCUSSION AND CONCLUSION: The latter result validates our prior methods for estimating the active state affinity constants of ligands, and our results on receptor coupling have relevance to studies investigating receptor-G protein interactions using fluorescence techniques.

International Union of Basic and Clinical Pharmacology. XC. multisite pharmacology: recommendations for the nomenclature of receptor allosterism and allosteric ligands.

Allosteric interactions play vital roles in metabolic processes and signal transduction and, more recently, have become the focus of numerous pharmacological studies because of the potential for discovering more target-selective chemical probes and therapeutic agents. In addition to classic early studies on enzymes, there are now examples of small molecule allosteric modulators for all superfamilies of receptors encoded by the genome, including ligand- and voltage-gated ion channels, G protein-coupled receptors, nuclear hormone receptors, and receptor tyrosine kinases. As a consequence, a vast array of pharmacologic behaviors has been ascribed to allosteric ligands that can vary in a target-, ligand-, and cell-/tissue-dependent manner. The current article presents an overview of allostery as applied to receptor families and approaches for detecting and validating allosteric interactions and gives recommendations for the nomenclature of allosteric ligands and their properties.