Computer modeling of myosin binding protein C and its effects on cardiac contraction
肌球蛋白结合蛋白 C 的计算机建模及其对心脏收缩的影响
基本信息
- 批准号:10371076
- 负责人:
- 金额:$ 55.17万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-04-01 至 2024-03-31
- 项目状态:已结题
- 来源:
- 关键词:ActinsAmericanAnimal ExperimentsAnimal ModelAnimalsAutomobile DrivingBindingBiologyCardiacCardiovascular PhysiologyCellsClinicalClinical TrialsComputer ModelsComputersCoupledDNA Sequence AlterationDataDepressed moodDevelopmentDilated CardiomyopathyDiseaseDisease ProgressionEFRACEngineeringFailureFiberFunctional disorderGeneticGoalsHeadHeartHeart DiseasesHeart HypertrophyHeart failureHumanImpairmentMeasurementMeasuresMechanicsModelingMolecularMolecular TargetMusMuscleMuscle ProteinsMuscle functionMutant Strains MiceMutationMyocardiumMyosin ATPasePatientsPhosphorylationPhosphorylation SitePhysiciansProteinsPublic HealthPumpRecombinantsRelaxationSarcomeresSiteTestingTherapeuticThin FilamentVariantViralbasecostdesigneffective therapyexperimental studygain of function mutationhemodynamicshuman modelimprovedin silicoin vivomathematical modelmolecular targeted therapiesmouse modelmulti-scale modelingmutantmyosin-binding protein Cnew therapeutic targetnovel therapeuticspersonalized medicinepreservationreconstitutionresponsescreeningtherapeutically effectivetherapy developmenttreatment optimizationtreatment planningviral gene delivery
项目摘要
PROJECT ABSTRACT
In this project, we will develop a new computational modeling framework capable of designing targeted
molecular therapies for heart failure. Impairment of cardiac muscle function constitutes a major clinical problem
and comes in many forms. For example, sarcomere-level contraction is depressed in many of the 3 million
Americans who have Heart Failure with reduced Ejection Fraction (HFrEF). The opposite issue, excessive
activity of muscle proteins, can contribute to Heart Failure with preserved Ejection Fraction (HFpEF) by slowing
relaxation and stiffening the ventricle. Genetic mutations to sarcomeric proteins afflict another 700,000
Americans. Gain of function mutations typically produce cardiac hypertrophy while loss of molecular function
results in dilated cardiomyopathy. Patients and physicians urgently need better therapies for these conditions
but the clinical trials used to test potential new strategies cost ~$1 billion and are plagued by high failure rates.
This project tests the hypothesis that computer modeling can help to overcome these challenges by efficiently
predicting the therapeutic potential of novel drug targets in the context of each different form of heart failure.
The ultimate goal would be to screen a wide range of molecular strategies in silico and then select the most
promising options for animal experiments and/or clinical trials. In the long term, it might even be possible to
implement patient-specific computer modeling to help optimize treatment plans. The more immediate impacts
would include reducing costs and focusing trials on the most effective molecular targets.
The first step is to establish the feasibility of a modeling-driven pipeline using murine models of heart failure
(HF) and a single molecular target. Recent studies show that sarcomere-focused treatments for HF have
significant promise and that myosin-binding protein-C (MyBPC) could be a particularly effective target. This is
because MyBPC can both enhance and inhibit contractility with the net regulatory effect depending on the
phosphorylation status of three known residues. Phospho-variants of MyBPC could therefore be engineered to
increase or decrease cardiac contractility as desired. In our view, the main roadblock hindering MyBPC's
development as a potential new therapy is incomplete understanding of the molecule's mechanistic action.
Specifically, it is not yet known precisely how the phosphorylation status of each residue modulates MyBPC's
ability to enhance function (by activating the thin filament) and depress function (by restricting the mobility of
detached myosin heads).
The goals of this project are therefore to (1) develop a modeling framework that establishes how site-specific
MyBPC phosphorylation impacts contractile function, (2) validate the model using sarcomere to animal-level
experiments, and (3) test the pipeline's ability to predict effective therapeutic strategies by combining in silico
screening and viral delivery of computer-selected mutant MyBPC.
项目摘要
在这个项目中,我们将开发一个新的计算建模框架,能够设计有针对性的
心力衰竭的分子疗法心肌功能的损害构成了一个主要的临床问题
有很多种形式例如,在300万名患者中,
患有射血分数降低的心力衰竭(HFrEF)的美国人相反,过度
肌肉蛋白的活性,可通过减缓射血分数保留(HFpEF)而导致心力衰竭。
使心室松弛和变硬。肌节蛋白的基因突变折磨着另外70万人
美国人功能获得性突变通常会导致心肌肥大,而分子功能丧失
导致扩张型心肌病患者和医生迫切需要更好的治疗这些条件
但用于测试潜在新策略的临床试验耗资约10亿美元,并受到高失败率的困扰。
这个项目测试的假设,计算机建模可以帮助克服这些挑战,有效地
预测新型药物靶点在每种不同形式心力衰竭中的治疗潜力。
最终的目标将是通过计算机筛选广泛的分子策略,然后选择最多的
动物实验和/或临床试验的有前途的选择。从长远来看,甚至有可能
实施患者特定的计算机建模,以帮助优化治疗计划。更直接的影响
这将包括降低成本和将试验集中在最有效的分子靶点上。
第一步是使用心力衰竭小鼠模型建立建模驱动的管道的可行性
(HF)和单个分子靶点。最近的研究表明,肌节为重点的治疗HF,
肌球蛋白结合蛋白-C(MyBPC)可能是一个特别有效靶点。这是
因为MyBPC可以增强和抑制收缩性,其净调节作用取决于
三个已知残基的磷酸化状态。因此,MyBPC的磷酸化变体可以被工程化,
根据需要增加或减少心脏收缩力。在我们看来,阻碍MyBPC
作为一种潜在的新疗法的发展是不完整的分子的机械作用的理解。
具体来说,目前尚不清楚每个残基的磷酸化状态如何调节MyBPC
增强功能(通过激活细丝)和抑制功能(通过限制
分离的肌球蛋白头)。
因此,本项目的目标是(1)开发一个建模框架,以确定如何针对特定地点
MyBPC磷酸化影响收缩功能。(2)在动物水平上验证肌节模型
实验,和(3)测试管道的能力,预测有效的治疗策略,通过结合在硅片
计算机选择的突变MyBPC的筛选和病毒递送。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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STUART G CAMPBELL其他文献
STUART G CAMPBELL的其他文献
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{{ truncateString('STUART G CAMPBELL', 18)}}的其他基金
Establishing and reversing the functional consequences of Titin truncation mutations
建立并逆转肌联蛋白截断突变的功能后果
- 批准号:
10510011 - 财政年份:2022
- 资助金额:
$ 55.17万 - 项目类别:
Establishing and reversing the functional consequences of Titin truncation mutations
建立并逆转肌联蛋白截断突变的功能后果
- 批准号:
10640157 - 财政年份:2022
- 资助金额:
$ 55.17万 - 项目类别:
Computer modeling of myosin binding protein C and its effects on cardiac contraction
肌球蛋白结合蛋白 C 的计算机建模及其对心脏收缩的影响
- 批准号:
9903433 - 财政年份:2019
- 资助金额:
$ 55.17万 - 项目类别:
Revealing Pathomechanisms of Mutant TPM1 Through a Hybrid Computational-Experimental Approach
通过混合计算-实验方法揭示突变 TPM1 的病理机制
- 批准号:
10358783 - 财政年份:2017
- 资助金额:
$ 55.17万 - 项目类别:
Revealing Pathomechanisms of Mutant TPM1 Through a Hybrid Computational-Experimental Approach
通过混合计算-实验方法揭示突变 TPM1 的病理机制
- 批准号:
9398261 - 财政年份:2017
- 资助金额:
$ 55.17万 - 项目类别:
Revealing Pathomechanisms of Mutant TPM1 Through a Hybrid Computational-Experimental Approach
通过混合计算-实验方法揭示突变 TPM1 的病理机制
- 批准号:
9983135 - 财政年份:2017
- 资助金额:
$ 55.17万 - 项目类别:
Revealing Pathomechanisms of Mutant TPM1 Through a Hybrid Computational-Experimental Approach
通过混合计算-实验方法揭示突变 TPM1 的病理机制
- 批准号:
10221767 - 财政年份:2017
- 资助金额:
$ 55.17万 - 项目类别:
Computational Pipeline for Identification of Disease-Causing Variants in Genes of the Cardiac Sarcomere
用于鉴定心脏肌节基因致病变异的计算流程
- 批准号:
10736459 - 财政年份:2017
- 资助金额:
$ 55.17万 - 项目类别:
Engineered Tissue for Biomechanical Phenotyping of Cardiomyopathy Patients
用于心肌病患者生物力学表型分析的工程组织
- 批准号:
8974854 - 财政年份:2014
- 资助金额:
$ 55.17万 - 项目类别:
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