Integrative structural analysis of human insulin degrading enzyme

项目摘要/总结： 淀粉样蛋白肽的聚集体，如淀粉样蛋白原纤维具有高度细胞毒性，如淀粉样蛋白的作用所例示。 阿尔茨海默病中的B（Aβ）。为了维持健康的蛋白质组，许多蛋白酶靶向单体蛋白质。 这是淀粉样肽的一种形式，因为这种形式既能促进淀粉样纤维的播种又能延长。胰岛素降解 酶（IDE）是一种110 kDa的金属蛋白酶，可降解各种淀粉样肽，包括Aβ和三种 血糖调节激素，即胰岛素、胰淀素和胰高血糖素。IDE中的缺陷改变了进展 2型糖尿病和阿尔茨海默氏病的动物模型，并与这些疾病在人类。 IDE抑制剂可以控制小鼠的血糖水平，并有望用于治疗糖尿病。的一个关键 IDE催化循环中的一个重要步骤是在降解之前选择性识别和解折叠淀粉样肽。 我们的前提是，未充分研究的IDE构象动力学提供了力学基础， 肽底物的解折叠。因此，我们可以利用我们对这些过程的理解， 调节IDE对特定底物的活性。我们的长期目标是阐明 IDE如何选择性地识别淀粉样肽并利用这些知识开发新的IDE的细节- 基础疗法来改善人类状况。为了实现这一目标，我们整合了整体结构， 测定和基于溶液的方法来显示IDE是含蛋白酶的室的成员， 又称隐酶，一个利用相当大的催化室吞噬单体淀粉样肽的家族。我们有 我还生成了一个工作模型，解释了IDE如何使用两个关键的构象开关来选择性地 降解淀粉样肽。本申请的目的是确定关键的未解决的构象 阐述并探讨IDE在催化循环过程中的构象动力学， 结构方法。然后，我们将结合联合收割机MD模拟和筛选，以确定调整 催化活性和选择性。我们的研究理论基础是， IDE的功能将使我们能够通过工程或新的小分子来调节其活性， 最终促进基于IDE的治疗的设计，以对抗蛋白质稳态失衡。我们会利用时间- 解决了cryoEM和SAXS，以了解关键时间内底物识别的结构基础 IDE第一次遇到基质时的窗口与高级cryoEM图像处理算法相结合 和MD模拟，以解决IDE运动如何展开生理相关的基板。我们将应用 从底物识别和展开研究中获得的知识，以开发筛选策略， 通过IDE选择性调节Ab降解的方法。这项工作将大大提高我们的 通过定义生理相关条件下的关键构象状态来理解IDE催化循环 条件，并提供了一个平台，融合一体化的结构分析和MD模拟的发现 创新的酶调节策略作为新型IDE疗法的发展基础。

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.