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 心力衰竭的分子疗法心肌功能损害是临床上的一个主要问题 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的主要障碍 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。 具体地说，目前还不清楚每个残基的磷酸化状态如何调节MyBPC的磷酸化水平。 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，建立如何网站特定 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。

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.