Structural Dynamics of Cardiac Myosin-Binding Protein C Regulation

项目摘要 肥厚型心肌病（HCM）是一种相对常见的疾病，每500人中就有1人患病 也是年轻人和运动员猝死的主要原因。HCM是一种未满足的医疗需求， 没有FDA批准的治疗方法约40%的HCM病例与编码HCM的基因突变有关。 心肌肌球蛋白结合蛋白C（MyBP-C）。MyBP-C是一种厚的免疫相关蛋白， 正常的心肌性能;它位于肌节的中心，以调节 肌球蛋白横桥和肌动蛋白细丝，负责力的发展。我们先前已经 表明MyBP-C的磷酸化增加增强肌动蛋白-肌球蛋白相互作用， 心肌收缩动力学加速，而磷酸化减少导致肌动蛋白-肌球蛋白减少 接近和减速收缩。然而，MyBP-C磷酸化是如何改变细胞内蛋白质的表达的， 结构动力学与肌动蛋白和/或肌球蛋白的相互作用，以调节正常人的力量发展 心肌或突变如何改变最终导致HCM发病的功能。我们有 开发了创新的生物物理工具，首次能够评估：（1） MyBP-C，（2）它如何与肌肉中的肌动蛋白和/或肌球蛋白相互作用，以及（3）这些相互作用如何受到 磷酸化和已知的病理性突变。我们将测试中心假设，即磷酸化和 N-末端MyBP-C的HCM突变改变MyBP-C的功能上显著的结构特性， 与肌动蛋白和肌球蛋白的相互作用。目的1将评估磷酸化，HCM突变， 与肌动蛋白或肌球蛋白结合对MyBP-C结构动力学的影响。光谱方法将被用来检测 由于磷酸化、HCM突变和肌动蛋白/肌球蛋白引起的MyBP-C内的构象变化（结构） binding（function）.分子动力学（MD）模拟将作为一种补充方法。目的2 将确定MyBP-C磷酸化和HCM突变体如何影响关键蛋白的邻近性和动力学。 心肌蛋白我们将利用定点探针技术在皮肤（脱膜）的心脏纤维 以确定磷酸化/突变体如何影响蛋白质结构/原位相互作用以调节收缩性。 所提出的研究在真实的时间内捕获结构动力学，并在真实的心肌空间内解决相互作用 使用新颖的高分辨率方法。这些目标是一个逐步发展的新模式， 研究收缩周期中正常和突变的MyBP-C。这种模式涉及到监测距离 蛋白质上的点与生理条件下这些距离的顺序（或无序）之间的关系， 相互作用的蛋白质和功能心肌。并非所有HCM突变体都影响MyBP-C的相同功能。 时间分辨荧光数据组件，薄/厚灯丝动力学，力学和模拟将 用于将突变体分离到可识别的箱中，为识别基于机制的疗法奠定基础， 专门治疗不同类型的突变。

PROJECT SUMMARY Hypertrophic cardiomyopathy (HCM) is a relatively common disease affecting more than 1 in 500 individuals and the leading cause of sudden death in young individuals and athletes. HCM is an unmet medical need with no FDA-approved treatments. ~40% of all HCM cases are associated with mutations in the gene encoding cardiac myosin-binding protein C (MyBP-C). MyBP-C is a thick filament-associated protein that is critical for normal myocardial performance; it is centrally positioned in the sarcomere to regulate interactions between myosin cross-bridges and actin thin filaments that are responsible for force development. We have previously demonstrated that increased phosphorylation of MyBP-C enhances actin-myosin interactions leading to accelerated contraction kinetics in myocardium, whereas reduced phosphorylation led to reduced actin-myosin proximity and decelerated contraction. However, it is not understood how MyBP-C phosphorylation alters the structural dynamics of its interactions with actin and/or myosin to modulate force development in normal myocardium or how mutations alter functions that ultimately contribute to HCM pathogenesis. We have developed innovative biophysical tools that, for the first time, enable evaluation of: (1) the structural dynamics of MyBP-C, (2) how it interacts with actin and/or myosin in muscle, and (3) how these interactions are affected by phosphorylation and known pathologic mutations. We will test the central hypothesis that phosphorylation and HCM mutations of N-terminal MyBP-C alter functionally significant structural properties of MyBP-C and interactions with actin and myosin. Aim 1 will evaluate the effects of phosphorylation, HCM mutations, and binding to actin or myosin on MyBP-C structural dynamics. Spectroscopic approaches will be employed to detect conformational changes (structure) within MyBP-C due to phosphorylation, HCM mutation, and actin/myosin binding (function). Molecular dynamics (MD) simulations will be applied as a complementary approach. Aim 2 will determine how MyBP-C phosphorylation and HCM mutants affect proximities and dynamics of key myocardial proteins. We will utilize site-directed probe technologies in skinned (demembranated) cardiac fibers to determine how phosphorylation/mutants affect protein structure/interactions in situ to regulate contractility. The proposed studies capture structural dynamics in real time and resolve interactions in real myocardial space using novel high-resolution approaches. These aims are a stepwise progression developing a new paradigm for studying normal and mutant MyBP-C during the contractile cycle. This paradigm involves monitoring distances between points on proteins and the order (or disorder) of those distances under physiological conditions, in interacting proteins and functioning myocardium. Not all HCM mutants impact the same functions of MyBP-C. Time-resolved fluorescence data components, thin/thick filament dynamics, mechanics, and simulations will be used to separate mutants into identifiable bins, setting the stage for identifying mechanistic-based therapies to specifically treat different classes of mutations.