Pharmacogenomics and antiarrhythmic therapy: An in silico investigation
Pharmacogenomics and antiarrhythmic therapy: An in silico investigation
批准号:
7788189
负责人:
COLLEEN E CLANCY
金额:
$30.6万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-04-15 至 2012-03-31
关键词:
AccountingAction PotentialsAddressAffectAffinityArrhythmiaBehaviorBindingBloodCardiacCell membraneCell modelCellsChargeComplexComputer SimulationCoupledDependenceDevelopmentDiagnosisDiffusionDrug Delivery SystemsDrug InteractionsDrug KineticsDrug ReceptorsDrug effect disorderEffectivenessEnvironmentFailureGenesGeneticGenetic MedicineGenotypeGoalsHeart BlockInterventionInvestigationIon ChannelIon Channel GatingKineticsLinkMembraneModelingMolecularMolecular ConformationMorphologyMovementMutationOutcomePathway interactionsPharmaceutical PreparationsPharmacodynamicsPharmacogenomicsPharmacological TreatmentPlasmaPlayPredispositionProcessPropertyProteinsProtocols documentationResearchResearch PersonnelRoleSimulateSpecificitySystemTestingTheoretical modelTherapeutic AgentsTimeTissue ModelTissuesbasechannel blockersdrug mechanismdrug testingimprovedmarkov modelmutantnovelpreventprogramsreceptorresponsesimulationstemtooltwo-dimensionalvirtualvirtual humanvoltage
中文摘要
描述(由申请人提供):心律失常的药物治疗是一个长期寻求但至今仍难以实现的目标。用药物治疗心律失常的疗效和结果不佳,部分原因是未能准确预测具有隐含复杂药效学的药物如何影响多成分相互作用的心脏细胞和组织。例如,将药物阻断心脏离子通道表示为减小的电流幅度过于简单化并且无法预测药物作用。相反,为了开发适当的心律失常管理药物干预措施,必须考虑多种因素,包括复杂的药物药代动力学、pH依赖性、电压依赖性、药物的构象特异性阻断和速率依赖性特性,以及药物与心律失常的多种机制和触发因素的相互作用。这些问题在过去十年中变得更加复杂,在此期间,遗传学的进展表明,基因也在决定心律失常的易感性和药物治疗的有效性方面发挥着作用。因此,现在很清楚,除了药效学之外,基因型也必须被视为心律失常药物治疗的一个因素。我们的目标是通过构建虚拟心脏细胞和组织中药物阻断的详细数学路径来开发新的理论方法,以弥补这一差距。我们研究的长期目的是开发一个框架,用于准确预测药物与心脏离子通道的相互作用,特别是预测突变和药物阻断对细胞和组织水平电行为的新兴影响。我们将实现以下三个具体目标: 1:开发一个理论框架来模拟心脏 Na 通道的药理学阻断 - 一个综合模型,包括 pH 依赖性分配、膜扩散、相互作用的构象状态特异性和 Na 通道阻断的电压依赖性。 2:目标 2:利用虚拟心脏细胞中的理论框架来检查正常或心律失常相关突变 Na 通道的 Na 通道阻断对细胞活性的影响。 3:使用组织水平模拟来测试药物基因组学、药物治疗和心律失常之间的关系。该提案的优点在于测试和预测用于诊断和治疗心律失常的药物干预结果的新颖方法,代表了虚拟药物测试系统的进展。
英文摘要
DESCRIPTION (provided by applicant): 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.
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