Computer modeling of myosin binding protein C and its effects on cardiac contraction

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 治疗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 有很多种形式。例如，300万人中的许多人肌节水平的收缩都受到抑制 美国心力衰竭患者的射血分数降低(HFrEF)。相反的问题，过度 肌肉蛋白的活性，可通过减慢射血分数(HFpEF)而导致心力衰竭 放松和使脑室僵硬。另有70万人因肌瘤蛋白基因突变而苦恼 美国人。功能突变的获得通常会导致心肌肥厚，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疾病的方法。 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。 该项目验证了这样的假设，即计算机建模可以通过高效地帮助克服这些挑战 在每种不同形式的心力衰竭的背景下预测新药物靶点的治疗潜力。 最终目标将是筛选电子计算机中广泛的分子策略，然后选择最 动物实验和/或临床试验的前景看好的选择。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 将包括降低成本和将试验集中在最有效的分子靶标上。 第一步是利用心力衰竭的小鼠模型建立模型驱动管道的可行性 (HF)和单个分子靶标。最近的研究表明，以肌节为中心的治疗心衰有 而且肌球蛋白结合蛋白-C(MyBPC)可能是一个特别有效的靶点。这是 因为MyBPC既可以增强收缩，也可以抑制收缩，其净调节效果取决于 三个已知残基的磷酸化状态。因此，MyBPC的磷酸化变体可以被改造成 根据需要增加或减少心脏的收缩能力。在我们看来，阻碍MyBPC的主要障碍是 作为一种潜在的新疗法的发展是对分子的机械作用的不完全理解。 具体地说，目前还不清楚每个残基的磷酸化状态如何调节MyBPC的 能够增强功能(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，该项目的目标是(1)开发一个建模框架，该框架建立如何针对特定地点 MyBPC的磷酸化影响收缩功能，(2)用肌节在动物水平上验证模型 实验，以及(3)测试管道通过结合硅胶预测有效治疗策略的能力 计算机选育突变体MyBPC的筛选和病毒传递

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.