Integrative structural analysis of human insulin degrading enzyme

项目摘要/摘要： 淀粉样多肽的聚集体，如淀粉样蛋白纤维，具有高度的细胞毒性，淀粉样蛋白的作用就是例证。 B(Aβ)在阿尔茨海默病中。为了维持健康的蛋白质组，许多蛋白酶针对单体。 淀粉样多肽是一种淀粉样多肽，因为这种形式可以促进淀粉样蛋白纤维的生长和伸长。胰岛素降解 酶是一种110kDa的金属蛋白水解酶，能降解多种淀粉样多肽，包括Aβ和3 血糖调节激素，即胰岛素、胰淀素和胰高血糖素。IDE中的缺陷改变了进程 在动物模型中，2型糖尿病和阿尔茨海默氏症的发病率很高，并与人类的这些疾病有关。 IDE抑制剂可以控制小鼠的血糖水平，并有望治疗糖尿病。其中一个关键是 IDE催化循环中的步骤是在降解之前选择性地识别和展开淀粉样多肽。 我们的前提是，未被充分研究的IDE构象动力学为 多肽底物的展开。因此，我们可以利用我们对这些过程的理解来选择性地 调节IDE对特定底物的活性。我们的长期目标是阐明分子 IDE如何选择性识别淀粉样多肽并利用这一知识开发新型IDE的细节- 以改善人类状况为基础的治疗。为了实现这一目标，我们整合了合奏结构 测定和基于溶液的方法以表明IDE是含有小室的蛋白酶的成员， 又名隐形酶家族，使用相当大的催化室来吞噬单体淀粉样多肽。我们有 还生成了一个工作模型，该模型解释了IDE如何使用两个关键的构象开关来选择性地 降解淀粉样多肽。我们这项应用的目标是确定关键的未解决的构象 应用最新集成技术研究IDE在催化循环中的构象动力学 结构性方法。然后，我们将结合MD模拟和筛选来确定调制 IDE的催化活性和选择性。我们研究的基本原理是，对监管有更深入的理解 而IDE的功能将允许我们通过工程或新的小分子和 最终促进基于IDE的疗法的设计，以对抗蛋白质平衡失衡。我们会用时间- 了解关键时间内底物识别的结构基础 IDE首次接触衬底时的窗口与先进的CryoEM图像处理算法相结合 以及MD模拟，以解决IDE运动如何展开生理相关的衬底。我们将应用 从底物识别和展开研究中获得的知识，以制定筛选策略以识别 方法用IDE选择性地调节抗体的降解。这项工作将大大增强我们的 通过在生理相关条件下定义关键构象状态来理解IDE催化循环 并提供了一个平台，将综合结构分析和MD模拟融合在一起，以期发现 创新的酶调节策略作为基于IDE的新型疗法的开发基础。

Project Abstract/Summary: Aggregates of amyloid peptides, such as amyloid fibrils are highly cytotoxic, as exemplified by the role of amyloid b (Aβ) in Alzheimer's disease. To maintain a healthy proteome, a number of proteases target the monomeric form of amyloid peptides because this form fuels both seeding and elongation of amyloid fibrils. Insulin degrading enzyme (IDE) is a 110 kDa metalloprotease that degrades various amyloid peptides, including Aβ and three blood glucose-regulating hormones, namely insulin, amylin, and glucagon. Defects in IDE alter the progression of type 2 diabetes mellitus and Alzheimer’s disease in animal models and are linked to these diseases in humans. IDE inhibitors can control blood glucose level in mice and hold promise for treating diabetes. One of the key steps in the IDE catalytic cycle is the selective recognition and unfolding of amyloid peptides prior to degradation. Our premise is that the understudied conformational dynamics of IDE provide the mechanical basis for the unfolding of peptide substrates. Thus, we can leverage our understanding of these processes to selectively modulate the activity of IDE towards specific substrates. Our long-term goals are to elucidate the molecular details of how IDE selectively recognizes amyloid peptides and utilize this knowledge to develop novel IDE- based therapies to improve the human condition. Toward this goal, we have integrated ensemble structural determination and solution-based methods to show that IDE is a member of the chamber-containing protease, aka cryptidase, family that uses a sizable catalytic chamber to engulf monomeric amyloid peptides. We have also generated a working model that explains how IDE uses two key conformational switches to selectively degrade amyloid peptides. Our objectives for this application are to determine key unsolved conformational states and probe the conformational dynamics of IDE during the catalytic cycle by applying state-of-art integrative structural approaches. We will then combine MD simulation and screening to identify strategies to modulate the catalytic activity and selectivity of IDE. Our research rationale is that a deeper understanding of the regulation and functions of IDE will allow us to modulate its activity through engineering or novel small molecules and ultimately facilitate the design of IDE-based therapies to combat proteostatic imbalances. We will use time- resolved cryoEM and SAXS to understand the structural basis for substrate recognition during the key time window when IDE first encounters substrate in combination with advanced cryoEM image processing algorithms and MD simulation to address how IDE motions can unfold physiologically relevant substrates. We will apply the knowledge gained from the substrate recognition and unfolding studies to develop a screening strategy to identify methods to selectively modulate the degradation of Ab by IDE. This work will significantly enhance our understanding of the IDE catalytic cycle by defining key conformational states under physiologically relevant conditions and offer a platform to merge integrative structural analysis and MD simulation towards the discovery of innovative enzyme modulating strategies as the developmental foundation of novel IDE-based therapies.