Pharmacological treatment of cardiac arrhythmia is a long sought and as yet elusive goal. Poor efficacy and outcomes in treating arrhythmia with drugs is due, in part, to failure to accurately predict how drugs with implicitly complex pharmacodynamics affect multi-component interactive cardiac cells and tissues. For example, a representation of drug block of cardiac ion channels as reduced current amplitude is overly simplistic and fails to predict drug effects. Rather, multiple factors including complex drug pharmacokinetics, pH dependence, voltage dependence, conformation-specific block and rate-dependent properties of drugs, as well drug interaction with the multiple mechanisms and triggers of arrhythmia must be considered for development of appropriate pharmacological intervention for arrhythmia management. These issues have been further complicated in the last decade, during which genetic advances have revealed that genes also play a role in determining arrhythmia susceptibility and effectiveness of drug treatment. As a result, it is now clear that, in addition to pharmacodynamics, genotype must be considered as a factor in pharmacological management of arrhythmia. Our goal is to develop novel theoretical approaches through the construction of detailed mathematical pathways of drug block in virtual cardiac cells and tissues to bridge this gap. The long-term purpose of our studies is to develop a framework for accurate prediction of drug interaction with cardiac ion channels, and especially, to predict the emergent effects of mutations and drug block on cellular and tissue level electrical behavior. We will address the following three specific aims: 1: To develop a theoretical framework to simulate pharmacological block of cardiac Na+- channels - A comprehensive model that includes pH dependent partitioning, membrane diffusion, conformation-state specificity of interaction and voltage dependence of Na+ channel block. 2:
AIM 2 : To utilize the theoretical framework in virtual cardiac cells to examine the effects of Na+ channel block of normal or arrhythmia linked mutant Na+ channels on cell activity. 3: To test, using tissue level simulations, the relationship between pharmacogenomics, drug treatment and arrhythmia. The merit of this proposal lies in the novelty of the approach to test and predict the outcomes of drug interventions intended for diagnosis and treatment of cardiac arrhythmia and represents progress towards a virtual drug testing system.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
3R01HL085592-04S1
Application #
8048305
Study Section
Electrical Signaling, Ion Transport, and Arrhythmias Study Section (ESTA)
Program Officer
Lathrop, David A
Project Start
2007-04-15
Project End
2012-06-30
Budget Start
2010-04-01
Budget End
2012-06-30
Support Year
4
Fiscal Year
2009
Total Cost
$181,066
Indirect Cost
Name
University of California Davis
Department
Pharmacology
Type
Schools of Medicine
DUNS #
047120084
City
Davis
State
CA
Country
United States
Zip Code
95618
DeMarco, K R; Clancy, C E (2016) Cardiac Na Channels: Structure to Function. Curr Top Membr 78:287-311
Yang, Pei-Chi; Moreno, Jonathan D; Miyake, Christina Y et al. (2016) In silico prediction of drug therapy in catecholaminergic polymorphic ventricular tachycardia. J Physiol 594:567-93
Kurokawa, Junko; Kodama, Masami; Clancy, Colleen E et al. (2016) Sex hormonal regulation of cardiac ion channels in drug-induced QT syndromes. Pharmacol Ther 168:23-28
Perissinotti, Laura L; Guo, Jiqing; De Biase, Pablo M et al. (2015) Kinetic model for NS1643 drug activation of WT and L529I variants of Kv11.1 (hERG1) potassium channel. Biophys J 108:1414-1424
Romero, Lucia; Trenor, Beatriz; Yang, Pei-Chi et al. (2015) In silico screening of the impact of hERG channel kinetic abnormalities on channel block and susceptibility to acquired long QT syndrome. J Mol Cell Cardiol 87:271-82
Romero, Lucia; Trenor, Beatriz; Yang, Pei-Chi et al. (2014) In silico screening of the impact of hERG channel kinetic abnormalities on channel block and susceptibility to acquired long QT syndrome. J Mol Cell Cardiol 72:126-37
Yarov-Yarovoy, Vladimir; Allen, Toby W; Clancy, Colleen E (2014) Computational Models for Predictive Cardiac Ion Channel Pharmacology. Drug Discov Today Dis Models 14:3-10
Moreno, Jonathan D; Yang, Pei-Chi; Bankston, John R et al. (2013) Ranolazine for congenital and acquired late INa-linked arrhythmias: in silico pharmacological screening. Circ Res 113:e50-e61
Yang, Pei-Chi; Clancy, Colleen E (2012) In silico Prediction of Sex-Based Differences in Human Susceptibility to Cardiac Ventricular Tachyarrhythmias. Front Physiol 3:360
Lewin, Naomi; Aksay, Emre; Clancy, Colleen E (2012) Computational modeling reveals dendritic origins of GABA(A)-mediated excitation in CA1 pyramidal neurons. PLoS One 7:e47250

Showing the most recent 10 out of 25 publications