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：
9903433
负责人：
STUART G CAMPBELL
金额：
$ 55.12万
依托单位：
CASE WESTERN RESERVE UNIVERSITY
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 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9903433
关键词：
Actins American Animal Experiments Animal Model Animals Automobile Driving Binding Biology Cardiac Cardiovascular Physiology Cells Clinical Clinical Trials Computer Models Computers Coupled DNA Sequence Alteration Data Depressed mood Development Dilated Cardiomyopathy Disease Disease Progression EFRAC Engineering Failure Fiber Functional disorder Genetic Goals Head Heart Heart Diseases Heart Hypertrophy Heart failure Human Impairment Measurement Measures Mechanics Modeling Molecular Molecular Target Mus Muscle Muscle Proteins Muscle function Mutant Strains Mice Mutation Myocardium Myosin ATPase Patients Phosphorylation Phosphorylation Site Physicians Proteins Public Health Pump Recombinants Relaxation Sarcomeres Site Testing Therapeutic Thin Filament Treatment Efficacy Variant Viral base cost design effective therapy experimental study gain of function mutation hemodynamics human model improved in silico in vivo mathematical model molecular targeted therapies mouse model multi-scale modeling mutant myosin-binding protein C new therapeutic target novel therapeutics personalized medicine preservation reconstitution response screening therapy development treatment optimization treatment planning viral 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。心肌功能受损是一个主要的临床问题并且有多种形式。例如，在 300 万人中，许多人的肌节水平收缩受到抑制。患有射血分数降低 (HFrEF) 心力衰竭的美国人。相反的问题，过度肌肉蛋白的活性，可通过减缓射血分数（HFpEF）导致心力衰竭心室松弛和僵硬。肌节蛋白的基因突变影响了另外 70 万人的健康美国人。功能获得突变通常会导致心脏肥大，而分子功能丧失结果导致扩张型心肌病。患者和医生迫切需要更好的治疗方法来治疗这些疾病但用于测试潜在新策略的临床试验耗资约 10 亿美元，并且失败率很高。该项目测试了以下假设：计算机建模可以通过有效地帮助克服这些挑战预测新药物靶点在每种不同形式的心力衰竭中的治疗潜力。最终目标是通过计算机筛选各种分子策略，然后选择最适合的分子策略。动物实验和/或临床试验的有希望的选择。从长远来看，甚至有可能实施针对患者的计算机建模以帮助优化治疗计划。更直接的影响将包括降低成本并将试验重点放在最有效的分子靶标上。第一步是利用小鼠心力衰竭模型建立建模驱动管道的可行性 (HF) 和单分子靶标。最近的研究表明，以肌节为重点的心力衰竭治疗方法肌球蛋白结合蛋白-C (MyBPC) 可能是一个特别有效的靶点。这是因为 MyBPC 既可以增强也可以抑制收缩性，其净调节效果取决于三个已知残基的磷酸化状态。因此，MyBPC 的磷酸变体可以被设计为根据需要增加或减少心肌收缩力。我们认为，阻碍 MyBPC 的主要障碍作为一种潜在的新疗法的开发是对该分子机制作用的不完全理解。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（通过限制细胞的活动性）的能力分离的肌球蛋白头）。因此，该项目的目标是 (1) 开发一个建模框架，用于确定特定站点如何 MyBPC 磷酸化影响收缩功能，(2) 使用肌节在动物水平验证模型实验，以及（3）通过计算机结合来测试管道预测有效治疗策略的能力计算机选择的突变体 MyBPC 的筛选和病毒传递。