DMREF: Collaborative Research: Helical Protein Assemblies by Design

DMREF：合作研究：螺旋蛋白质组装设计

• 批准号: 1533958
• 负责人: Edward Egelman
• 金额: $ 32万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1533958&HistoricalAwards=false
• 关键词: DMREF; Collaborative; Research; Helical; Protein

NON-TECHNICAL SUMMARYMolecular self-assembly is a fundamental principle of life, with cells having mastered this process to encode incredible diversity of function. Helical protein assemblies organize much of the intracellular and extracellular structure, and direct all movement. The ability to emulate such functions by designing synthetic protein assemblies would transform modern molecular science, with far-reaching applications including locomotion, controlled release, directional transport, dynamic switching, and shape-selective catalysis. However, structurally ordered supramolecular materials on the nanometer length-scale are the most challenging to rationally construct and the most difficult to structurally analyze. The size and structural complexity of these extended protein assemblies present a significant challenge to current computational design methods. The rules that govern protein-protein interactions are more complex and difficult to reliably predict than for DNA. In this project, a novel intellectual framework for the targeted design of synthetic protein assemblies at atomic-level accuracy will be established, validated, and made available to the research community. Enabled by the combined expertise of the three investigators involved, this approach will merge significant advances in modeling and computational design with never-before-possible experimental techniques for structural determination of protein assemblies at the atomic level. On the way to developing this framework, fundamental questions of acute significance to biology, chemistry, and materials science will be addressed: from development of an understanding of the functional roles of native biological assemblies to construction of synthetic assemblies for technological applications. Students (graduate and undergraduate), postdoctorals, and faculty involved in this project will gain experience in a variety of computational, synthetic, and analytical methods in research areas of fundamental technological interest that will prepare them well for future scientific careers. An exchange program between the three academic institutions (Emory University, University of Virginia, and Dartmouth College) will be established that will permit students and postdoctorals to become involved in the different aspects of this research project.TECHNICAL SUMMARYHelical protein assemblies in biological systems exhibit a rich portfolio of structure and function; capturing these within simpler and more tractable synthetic materials would amount to a major leap in molecular science. Recent technological advances in genome sequencing, bioinformatic analysis, near-atomic resolution cryo-EM structural determination, and computational protein design, in combination with extant synthetic and analytical methods, present an unprecedented opportunity to engineer novel protein assemblies that emulate and improve upon their native counter-parts. This project will employ protein designability, estimated on the basis of native structural representation, as a mechanism to promote and control association between folded protein motifs with an aim to create protein-based materials of defined structure and function. Designability in the context of protein engineering refers to robustness of a protein fold in sequence space. A proxy for designability is the frequency of occurrence of a structural motif within the Protein Data Bank (PDB). This approach will be employed to search for designable interfaces between protomers within the protein structural databank. The ultimate objective of the proposed research will be to define sequences based on simple secondary or tertiary structural elements that are competent for self-assembly into nano-scale materials with extended helical symmetry. Computational methods will be employed to interrogate the protein structural databank to identify designable interfaces within robust structural motifs. Suitable candidate sequences will be computationally optimized and synthesized. Proven biophysical methods will be employed initially to identify sequences with promising self-assembly behavior. State-of-the-art high-resolution structural analyses will be performed on these assemblies using Iterative Helical Real-Space Reconstruction (IHRSR) from cryo-EM images. Dramatic improvements in imaging hardware, reconstruction algorithms, and computational methods of structural refinement have provided rapid access to near-atomic resolution structures of native and synthetic helical assemblies. These analyses will inform future rounds of computational modeling and design, thus establishing a dynamic feedback loop between theory, synthesis, and advanced methods of structural analysis.

非技术性的分子自组装是生命的基本原理，细胞已经掌握了这一过程，编码了令人难以置信的多样化的功能。螺旋蛋白组合组织了细胞内和细胞外的大部分结构，并指导所有的运动。通过设计合成蛋白质组件来模拟这些功能的能力将改变现代分子科学，具有深远的应用，包括移动、控制释放、定向运输、动态切换和形状选择催化。然而，纳米尺度的结构有序超分子材料是最难合理构建和结构分析的材料。这些延伸的蛋白质组件的大小和结构复杂性对当前的计算设计方法提出了巨大的挑战。支配蛋白质-蛋白质相互作用的规则比DNA更复杂，也更难可靠地预测。在这个项目中，将建立一个新的智能框架，用于原子级精确的合成蛋白质组件的定向设计，并将其提供给研究界。在三位研究人员的共同专业知识的推动下，这种方法将把建模和计算设计方面的重大进步与前所未有的实验技术结合起来，在原子水平上确定蛋白质组件的结构。在开发这一框架的道路上，将解决对生物学、化学和材料科学具有重大意义的基本问题：从发展对天然生物组装的功能作用的理解到构建用于技术应用的合成组装。参与该项目的学生(研究生和本科生)、博士后和教职员工将在具有基本技术兴趣的研究领域获得各种计算、合成和分析方法的经验，这将为他们未来的科学职业做好准备。三个学术机构(埃默里大学、弗吉尼亚大学和达特茅斯学院)之间将建立一个交流计划，允许学生和博士后参与这项研究项目的不同方面。技术摘要生物系统中的螺旋蛋白质组件展示了丰富的结构和功能组合；在更简单、更容易处理的合成材料中捕获这些组件将是分子科学的一次重大飞跃。基因组测序、生物信息学分析、近原子分辨低温EM结构测定和计算蛋白质设计方面的最新技术进步，与现有的合成和分析方法相结合，为设计模仿和改进天然蛋白质组件的新型蛋白质组件提供了前所未有的机会。该项目将采用蛋白质可设计性，根据天然结构表示估计，作为促进和控制折叠蛋白质基序之间的联系的机制，目的是创造确定结构和功能的蛋白质材料。在蛋白质工程的背景下，可设计性指的是蛋白质折叠在序列空间中的稳健性。可设计性的一个指标是结构基序在蛋白质数据库(PDB)中出现的频率。这种方法将被用来在蛋白质结构数据库中搜索原始体之间的可设计界面。拟议研究的最终目标将是定义基于简单的二级或三级结构元素的序列，这些结构元素能够自组装成具有扩展螺旋对称性的纳米材料。将使用计算方法询问蛋白质结构数据库，以确定稳健结构基序中的可设计界面。将对合适的候选序列进行计算优化和合成。经过验证的生物物理方法将首先用于识别具有良好自组装行为的序列。最先进的高分辨率结构分析将在这些组件上使用迭代螺旋真实空间重建(IHRSR)从冷冻-EM图像。成像硬件、重建算法和结构改进的计算方法的显著改进为快速获得天然和合成螺旋组件的近原子分辨率结构提供了途径。这些分析将为未来几轮计算建模和设计提供信息，从而在理论、综合和先进的结构分析方法之间建立一个动态反馈回路。