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Coexistence of hERG current block and disruption of protein trafficking in ketoconazole-induced long QT syndrome.

ABSTRACT: BACKGROUND AND PURPOSE: Many drugs associated with acquired long QT syndrome (LQTS) directly block human ether-a-go-go-related gene (hERG) K(+) channels. Recently, disrupted trafficking of the hERG channel protein was proposed as a new mechanism underlying LQTS, but whether this defect coexists with the hERG current block remains unclear. This study investigated how ketoconazole, a direct hERG current inhibitor, affects the trafficking of hERG channel protein. EXPERIMENTAL APPROACH: Wild-type hERG and SCN5A/hNa(v) 1.5 Na(+) channels or the Y652A and F656C mutated forms of the hERG were stably expressed in HEK293 cells. The K(+) and Na(+) currents were recorded in these cells by using the whole-cell patch-clamp technique (23 degrees C). Protein trafficking of the hERG was evaluated by Western blot analysis and flow cytometry. KEY RESULTS: Ketoconazole directly blocked the hERG channel current and reduced the amount of hERG channel protein trafficked to the cell surface in a concentration-dependent manner. Current density of the hERG channels but not of the hNa(v) 1.5 channels was reduced after 48 h of incubation with ketoconazole, with preservation of the acute direct effect on hERG current. Mutations in drug-binding sites (F656C or Y652A) of the hERG channel significantly attenuated the hERG current blockade by ketoconazole, but did not affect the disruption of trafficking. CONCLUSIONS AND IMPLICATIONS: Our findings indicate that ketoconazole might cause acquired LQTS via a direct inhibition of current through the hERG channel and by disrupting hERG protein trafficking within therapeutic concentrations. These findings should be considered when evaluating new drugs.

SUBMITTER: Takemasa H

PROVIDER: S-EPMC2241789 | biostudies-other | 2008 Feb

REPOSITORIES: biostudies-other

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Project description:Accurate diagnosis of predisposition to long QT syndrome is crucial for reducing the risk of cardiac arrhythmias. In recent years, drug-induced provocative tests have proved useful to unmask some latent mutations linked to cardiac arrhythmias. In this study we expanded this concept by developing a prototype for a computational provocative screening test to reveal genetic predisposition to acquired long-QT syndrome (aLQTS). We developed a computational approach to reveal the pharmacological properties of IKr blocking drugs that are most likely to cause aLQTS in the setting of subtle alterations in IKr channel gating that would be expected to result from benign genetic variants. We used the model to predict the most potentially lethal combinations of kinetic anomalies and drug properties. In doing so, we also implicitly predicted ideal inverse therapeutic properties of K channel openers that would be expected to remedy a specific defect. We systematically performed "in silico mutagenesis" by altering discrete kinetic transition rates of the Fink et al. Markov model of human IKr channels, corresponding to activation, inactivation, deactivation and recovery from inactivation of IKr channels. We then screened and identified the properties of IKr blockers that caused acquired long QT and therefore unmasked mutant phenotypes for mild, moderate and severe variants. Mutant IKr channels were incorporated into the O'Hara et al. human ventricular action potential (AP) model and subjected to simulated application of a wide variety of IKr-drug interactions in order to identify the characteristics that selectively exacerbate the AP duration (APD) differences between wild-type and IKr mutated cells. Our results show that drugs with disparate affinities to conformation states of the IKr channel are key to amplify variants underlying susceptibility to acquired long QT syndrome, an effect that is especially pronounced at slow frequencies. Finally, we developed a mathematical formulation of the M54T MiRP1 latent mutation and simulated a provocative test. In this setting, application of dofetilide dramatically amplified the predicted QT interval duration in the M54T hMiRP1 mutation compared to wild-type.

Project description:Accurate diagnosis of predisposition to long QT syndrome is crucial for reducing the risk of cardiac arrhythmias. In recent years, drug-induced provocative tests have proved useful to unmask some latent mutations linked to cardiac arrhythmias. In this study we expanded this concept by developing a prototype for a computational provocative screening test to reveal genetic predisposition to acquired long-QT syndrome (aLQTS). We developed a computational approach to reveal the pharmacological properties of I(Kr) blocking drugs that are most likely to cause aLQTS in the setting of subtle alterations in I(Kr) channel gating that would be expected to result from benign genetic variants.Weused themodel to predict themost potentially lethal combinations of kinetic anomalies and drug properties. In doing so, we also implicitly predicted ideal inverse therapeutic properties of K channel openers that would be expected to remedy a specific defect. We systematically performed “in silico mutagenesis” by altering discrete kinetic transition rates of the Fink et al. Markov model of human I(Kr) channels, corresponding to activation, inactivation, deactivation and recovery from inactivation of I(Kr) channels. We then screened and identified the properties of I(Kr) blockers that caused acquired long QT and therefore unmasked mutant phenotypes formild,moderate and severe variants. Mutant I(Kr) channels were incorporated into the O'Hara et al. human ventricular action potential (AP) model and subjected to simulated application of a wide variety of I(Kr)-drug interactions in order to identify the characteristics that selectively exacerbate the AP duration (APD) differences between wild-type and I(Kr) mutated cells. Our results show that drugs with disparate affinities to conformation states of the I(Kr) channel are key to amplify variants underlying susceptibility to acquired long QT syndrome, an effect that is especially pronounced at slow frequencies. Finally, we developed a mathematical formulation of the M54T MiRP1 latent mutation and simulated a provocative test. In this setting, application of dofetilide dramatically amplified the predicted QT interval duration in the M54T hMiRP1 mutation compared to wild-type.

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Coexistence of hERG current block and disruption of protein trafficking in ketoconazole-induced long QT syndrome.

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