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.

非技术摘要分子自组装是生命的基本原理，细胞已经掌握了这一过程来编码令人难以置信的功能多样性。螺旋蛋白组装体组织了大部分细胞内和细胞外结构，并指导所有运动。通过设计合成蛋白质组装体来模拟此类功能的能力将改变现代分子科学，其影响深远的应用包括运动、控制释放、定向运输、动态切换和形状选择催化。然而，纳米长度尺度的结构有序超分子材料的合理构建最具挑战性，并且最难进行结构分析。这些扩展蛋白质组装体的大小和结构复杂性对当前的计算设计方法提出了重大挑战。与 DNA 相比，控制蛋白质-蛋白质相互作用的规则更加复杂且难以可靠预测。在该项目中，将建立、验证并提供一个新颖的智能框架，用于在原子级精度下对合成蛋白质组装体进行靶向设计。在三位研究人员的综合专业知识的支持下，该方法将把建模和计算设计方面的重大进步与在原子水平上蛋白质组装体结构测定的实验技术相结合。在开发该框架的过程中，将解决对生物学、化学和材料科学具有重要意义的基本问题：从对天然生物组件的功能作用的理解到构建用于技术应用的合成组件。参与该项目的学生（研究生和本科生）、博士后和教师将获得基础技术兴趣研究领域的各种计算、合成和分析方法的经验，这将为他们未来的科学职业生涯做好准备。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该研究项目的不同方面。 技术摘要生物系统中的螺旋蛋白组装体表现出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物质将相当于分子科学的重大飞跃。基因组测序、生物信息分析、近原子分辨率冷冻电镜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，为设计模拟和改进其天然蛋白质组装体提供了前所未有的机会对应部分。该项目将利用基于天然结构表征估计的蛋白质可设计性，作为促进和控制折叠蛋白质基序之间关联的机制，旨在创建具有明确结构和功能的基于蛋白质的材料。蛋白质工程背景下的可设计性是指序列空间中蛋白质折叠的稳健性。可设计性的指标是蛋白质数据库 (PDB) 中结构基序的出现频率。这种方法将用于搜索蛋白质结构数据库中原体之间的可设计界面。拟议研究的最终目标是定义基于简单二级或三级结构元素的序列，这些元素能够自组装成具有扩展螺旋对称性的纳米级材料。将采用计算方法来询问蛋白质结构数据库，以识别稳健结构基序内的可设计界面。合适的候选序列将通过计算优化和合成。最初将采用经过验证的生物物理方法来识别具有有希望的自组装行为的序列。将使用冷冻电镜图像的迭代螺旋实空间重建 (IHRSR) 对这些组件进行最先进的高分辨率结构分析。成像硬件、重建算法和结构细化计算方法的显着改进提供了对天然和合成螺旋组件的近原子分辨率结构的快速访问。这些分析将为未来几轮计算建模和设计提供信息，从而在结构分析的理论、综合和高级方法之间建立动态反馈循环。