Nanomanufacturing of Protein Macromolecular Frameworks Through an Integrated Bioengineering and Computational Approach

通过综合生物工程和计算方法纳米制造蛋白质大分子框架

• 批准号: 1922883
• 负责人: Masaki Uchida
• 金额: $ 49.85万
• 依托单位: California State University-Fresno Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-12-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1922883&HistoricalAwards=false
• 关键词: Nanomanufacturing; Protein; Macromolecular; Frameworks; Through

New materials with innovative functionalities are needed to build new and useful devices and systems that enrich our lives. Ordered three-dimensional arrays built from nanoscale building-blocks, often called superlattices, are exciting because new functionalities can emerge from the interactions between individual building-blocks. The use of proteins as building-blocks is a groundbreaking new direction because proteins exhibit a wide range of properties and behavior, including catalytic and immune activities, which are often difficult to realize in synthetic molecules. Making ordered materials by conventional protein crystallization is a laborious procedure and the ability to tailor the structure of protein crystals is limited. This award supports fundamental research to develop versatile and tunable approaches to manufacture superlattice materials constructed of proteins. The availability of these unique protein-based materials impacts diverse industries such as energy, biomedical and catalysis, which advances national welfare. This project uniquely integrates several disciplines including materials science, bioengineering and computational modeling. The integration of experimental and computational approaches in this project impacts research efforts of the Network for Computational Nanotechnology (NCN), synergistically. Alongside the scientific impact of the project, it also leverages the multi-disciplinary approach to promote students, including women and minorities, on this project by acquiring broad skills and knowledge and by providing a positive impact on science education.The research team envisions that protein cage nanoparticles and linker proteins, which bind non-covalently to symmetry-specific sites on the protein cages, are promising building-blocks for constructing a new class of protein superlattices, i.e. protein macromolecular frameworks. Protein cages have hollow spherical architectures composed of a distinct number of subunits with well-defined symmetry-specific sites. The investigators anticipate that specific binding geometries between protein cages and linkers result in highly regular network structures with a wide range of functionalities. The research team integrates bioengineering and computational modeling approaches to develop a range of linker molecules with different lengths and binding affinities to protein cages. By connecting the protein cages together through protein linkers, they are geometrically confined, thus forming highly regulated structures. The structure of the protein macromolecular frameworks is tunable through the selection of protein cages and specific linker proteins. Additionally, protein macromolecular frameworks have two types of unique spaces internally to accommodate cargo molecules. These are interior cavity of individual protein cages and interstitial space between protein cages within the lattice. The team demonstrates that various cargo molecules, such as enzymes, could be encapsulated inside of the protein cages. In this project, reversible incorporation and release of guest molecules are studied, which could lead protein macromolecular frameworks to practical applications such as drug delivery and catalysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

需要具有创新功能的新材料来构建丰富我们生活的新设备和系统。由纳米级建筑块建造的有序的三维阵列（通常称为超级峰顶）令人兴奋，因为从单个建筑块之间的相互作用中可以出现新功能。将蛋白质用作建筑块是一个开创性的新方向，因为蛋白质表现出广泛的特性和行为，包括催化和免疫活性，在合成分子中通常难以实现。通过常规蛋白质结晶制作有序的材料是一种费力的程序，并且量身定制蛋白质晶体结构的能力受到限制。该奖项支持基础研究，以开发多功能，可调的方法来制造由蛋白质构建的超晶格材料。这些独特的基于蛋白质材料的可用性会影响各种行业，例如能源，生物医学和催化，这会促进国家福利。该项目独特地整合了几个学科，包括材料科学，生物工程和计算建模。实验和计算方法在该项目中的整合会影响计算纳米技术网络（NCN）的研究工作。 Alongside the scientific impact of the project, it also leverages the multi-disciplinary approach to promote students, including women and minorities, on this project by acquiring broad skills and knowledge and by providing a positive impact on science education.The research team envisions that protein cage nanoparticles and linker proteins, which bind non-covalently to symmetry-specific sites on the protein cages, are promising building-blocks for constructing a new class of protein超晶格，即蛋白质大分子框架。蛋白质笼具有空心的球形体系结构，该结构由具有明确定义的对称位点的不同亚基组成。研究人员预计，蛋白质笼子和接头之间的特定结合几何形状会导致具有广泛功能范围的高规律网络结构。研究团队集成了生物工程和计算建模方法，以开发一系列连接器分子，其长度不同，并且与蛋白质笼子具有结合亲和力。通过通过蛋白接头将蛋白质笼一起连接在一起，它们被几何限制，从而形成高度调节的结构。蛋白质大分子框架的结构可以通过选择蛋白质笼和特定的接头蛋白来调节。此外，蛋白质大分子框架在内部具有两种独特的空间，可容纳货物分子。这些是晶格内蛋白质笼之间的单个蛋白质笼子的内部腔和间质空间。该团队表明，可以将各种货物分子（例如酶）封装在蛋白质笼中。在该项目中，研究了来宾分子的可逆掺入和释放，这可能会导致蛋白质大分子框架进行实用的应用，例如药物输送和催化。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查审查的审查标准来通过评估来通过评估来获得支持的。

项目成果

Bioinspired Approaches to Self-Assembly of Virus-like Particles: From Molecules to Materials

• DOI: 10.1021/acs.accounts.2c00056
• 发表时间: 2022-05-17
• 期刊: ACCOUNTS OF CHEMICAL RESEARCH
• 影响因子: 18.3
• 作者: Douglas, Trevor;Wang, Yang
• 通讯作者: Wang, Yang

Protein docking model evaluation by 3D deep convolutional neural networks

• DOI: 10.1093/bioinformatics/btz870
• 发表时间: 2020-04-01
• 期刊: BIOINFORMATICS
• 影响因子: 5.8
• 作者: Wang, Xiao;Terashi, Genki;Kihara, Daisuke
• 通讯作者: Kihara, Daisuke

Harnessing physicochemical properties of virus capsids for designing enzyme confined nanocompartments.

• DOI: 10.1016/j.coviro.2021.12.012
• 发表时间: 2022-03
• 期刊: Current opinion in virology
• 影响因子: 5.9
• 作者: Uchida M;Manzo E;Echeveria D;Jiménez S;Lovell L
• 通讯作者: Lovell L

Higher-Order VLP-Based Protein Macromolecular Framework Structures Assembled via Coiled-Coil Interactions

• DOI: 10.1021/acs.biomac.3c00410
• 发表时间: 2023-07-19
• 期刊: BIOMACROMOLECULES
• 影响因子: 6.2
• 作者: Hewagama，Nathasha D.;Uchida，Masaki;Douglas，Trevor
• 通讯作者: Douglas，Trevor

Multilayered Ordered Protein Arrays Self-Assembled from a Mixed Population of Virus-like Particles

由病毒样颗粒混合群自组装的多层有序蛋白质阵列

• DOI: 10.1021/acsnano.1c11272
• 发表时间: 2022
• 期刊: ACS Nano
• 影响因子: 17.1
• 作者: Uchida, Masaki;Brunk, Nicholas E.;Hewagama, Nathasha D.;Lee, Byeongdu;Prevelige, Peter E.;Jadhao, Vikram;Douglas, Trevor
• 通讯作者: Douglas, Trevor