Intrinsically Disordered Proteins as Sensors of Membrane Curvature

本质上无序的蛋白质作为膜曲率的传感器

• 批准号: 9788761
• 负责人: Wade F Zeno
• 金额: $ 6.16万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-08 至 2020-08-07
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9788761
• 关键词: Adaptor Signaling Protein; Affinity; Behavior; Binding; Biological Assay; Biological Sciences; Biophysics; C-terminal; Cell membrane; Cell physiology; Cellular biology; Chemical Engineering; Clathrin; Coupled; Cystic Fibrosis; Data; Defect; Detection; Diabetes Mellitus; Disease; Endocytosis; Ensure; Entropy; Faculty; Fluorescence Microscopy; Goals; Knowledge; Length; Lipids; Location; Mammalian Cell; Maps; Measures; Membrane; Membrane Protein Traffic; Mission; Modeling; Molecular Conformation; N-terminal; Phase; Physical Chemistry; Play; Polymers; Positioning Attribute; Process; Protein Biochemistry; Proteins; Public Health; Quantitative Microscopy; Research; Role; Site; Structure; Surface; Tertiary Protein Structure; Testing; Time; Total Internal Reflection Fluorescent; Training; United States National Institutes of Health; Vesicle; Water; Work; base; biophysical properties; experimental study; human disease; materials science; molecular modeling; physical science; post-doctoral training; preference; recruit; scaffold; sensor; skills; stoichiometry; three dimensional structure; trafficking

PROJECT SUMMARY Curved membrane structures such as endocytic pits and trafficking vesicles are essential to cellular physiology. Formation of these structures requires that the proteins involved are able to sense membrane curvature. Two structure-based mechanisms of curvature sensing are known: (i) curvature-matching by crescent-shaped BAR domains and (ii) membrane insertion by amphipathic helices. Recently, the postdoctoral applicant has discovered an additional curvature sensing mechanism that arises not from a specific structural motif, but instead from protein domains that lack a well-defined 3D structure – intrinsically disordered protein (IDP) domains. How can IDPs sense membrane curvature? Like a random polymer chain, highly water soluble IDPs seek to maximize chain entropy. Tethering polymers to flat surfaces restricts their conformation to a half-plane. In contrast, increasing the curvature of the substrate increases the polymer’s configurational entropy. As such, polymer-like IDPs should display a preference for curved membrane substrates. Because IDP domains are prevalent among endocytic proteins, their ability to sense membrane curvature could strongly impact the initiation and assembly of curved membrane structures. In addition, IDP domains involved in endocytosis are known to form interconnected protein networks, which could further amplify curvature sensing. Preliminary work shows that IDPs have 4-5 times greater affinity for highly curved membrane surfaces in comparison to flatter membranes, which is comparable to structure-based curvature sensing mechanisms. When an IDP and a structured curvature sensing domains were coupled within the same protein, an additional 4-fold increase in curvature sensitivity was observed, suggesting a synergistic relationship among the curvature sensors. The goal of the proposed work is to characterize the ability of IDPs to sense membrane curvature. Work in Aim 1 will evaluate the extent to which IDPs can sense membrane curvature, testing the working hypothesis that IDPs will partition preferentially to highly curved membrane surfaces to maximize chain entropy. Work in Aim 2 will compare curvature sensing by IDPs to sensing by structure-based mechanisms, testing the working hypothesis that entropically-driven curvature sensing by IDPs is comparable in magnitude to the mechanisms used by structured domains. Finally, work in Aim 3 will measure the role of protein networks in amplifying membrane curvature sensitivity, testing the working hypothesis that IDP-containing endocytic proteins cooperatively enhance membrane curvature sensitivity. Current understanding of membrane curvature sensing focusses on specific structural domains. In contrast, this work will be highly significant because it explores the paradigm-shifting idea that proteins lacking a defined structure, IDPs, serve as potent sensors of membrane curvature. The role IDP domains play in curvature sensing and protein network formation is an important, yet unexplored idea in membrane traffic, creating an opportunity to fill a key gap in existing knowledge.

弯曲的膜结构，如内吞凹和运输囊泡是必不可少的 到细胞生理学。这些结构的形成需要相关的蛋白质能够感知 膜曲率已知两种基于结构的曲率感测机制： 新月形BAR域和（ii）膜插入两亲性螺旋。近日 博士后申请人已经发现了一种额外的曲率感测机制，该机制不是由特定的 结构基序，而是来自缺乏明确定义的3D结构的蛋白质结构域-本质上是无序的 蛋白质（IDP）结构域。IDP如何感知膜曲率？就像一个随机的聚合物链， 可溶性IDP寻求最大化链熵。将聚合物束缚在平面上限制了它们的构象， 半飞机相比之下，增加基底的曲率增加了聚合物的构型。 熵因此，聚合物样IDP应显示出对弯曲膜基底的偏好。因为IDP 结构域是内吞蛋白中普遍存在的，它们感知膜曲率的能力可能强烈地影响细胞的功能。 影响弯曲膜结构的启动和组装。此外，涉及的IDP域 已知内吞作用形成互连的蛋白质网络，这可以进一步放大曲率传感。 初步工作表明，IDP对高度弯曲的膜表面具有4-5倍的亲和力， 与更平坦的膜相比，这与基于结构的曲率感测机制相当。当 一个IDP和一个结构化的曲率传感结构域在同一蛋白质内偶联，额外的4倍 观察到曲率敏感性增加，表明曲率之间存在协同关系 传感器.所提出的工作的目标是表征的能力的IDP感测膜曲率。工作 目标1中的研究将评估IDP能够感知膜曲率的程度，检验工作假设 IDP将优先分配到高度弯曲的膜表面以最大化链熵。工作 目标2将比较IDP的曲率感测与基于结构的机制的感测， 假设IDP的熵驱动曲率感知在幅度上与 使用结构化域。最后，目标3中的工作将测量蛋白质网络在放大 膜曲率敏感性，测试工作假设，含IDP的内吞蛋白 协同增强膜曲率敏感性。膜曲率传感的当前理解 专注于特定的结构域。相比之下，这项工作将是非常重要的，因为它探讨了 一种范式转变的想法，即缺乏确定结构的蛋白质，IDPs，作为膜的有效传感器 曲率IDP结构域在曲率传感和蛋白质网络形成中的作用是重要的，但 膜交通中未开发的想法，创造了一个机会，以填补现有知识的关键差距。