GOALI: Collaborative Proposal: Mechanistic Design of Aggregation Resistance in Multi-Domain Proteins

GOALI：合作提案：多域蛋白质抗聚集的机制设计

• 批准号: 1264554
• 负责人: Anne Robinson
• 金额: $ 25万
• 依托单位: Tulane University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1264554&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Proposal; Mechanistic; Design

Roberts/Robinson1264329/1264554 Non-native aggregation denotes a set of molecular processes by which a folded, biologically active protein becomes effectively locked into a ?misfolded? assembly or aggregate of proteins. Formation of these aggregates is a ubiquitous hurdle to successful over-expression, purification, and storage of recombinant proteins throughout the biotechnology and biopharmaceutical industries. This is particularly the case for multi-domain proteins, such as natural and designed antibodies, as well as for other predominantly-beta proteins. Predictive design of these more complex proteins is handicapped by limitations in the mechanistic understanding of key features of sequence and structure that control aggregation of multi-domain proteins. This project seeks to improve fundamental understanding of the mechanism(s) of multi-domain protein aggregation, so as to provide general design rules to engineer aggregation resistance into therapeutic proteins and other biotechnology products. This is a partnership between Amgen, Tulane University, and the University of Delaware through the National Science Foundation?s industry-university GOALI program. The work will focus on computational design of new antibody molecules that retain their known function (e.g., ligand binding) while greatly reducing their aggregation rates, and then experimentally characterizing the aggregation pathways to assure that the design predictions worked properly at a molecular level. From a broader perspective, the project focuses on creating new experimental and computational tools to better predict and control or even eliminate aggregates in protein pharmaceuticals and other biotechnology products. Doing so will decrease the cost of development for industrial scientists and engineers, and also decrease the time to market and any safety risks associated with protein aggregates in medical applications. The biopharmaceutical industry is one the fastest growing and attractive industries for growth of the U.S. job market requiring a highly trained workforce that will maintain international competitiveness. An indirect but equally important outcome of this project is the training of the next generation of industrial scientists and potential leaders for the industry, as well as development of new educational tools for more broad use throughout the technical community, and potentially for direct use in demonstrations in high school science courses such as chemistry, biochemistry, biology, and physics.

Roberts/Robinson1264329/1264554非本地聚集表示一组分子过程，通过该过程有效地将其折叠的生物活性蛋白有效地锁定在错误折叠中？蛋白质的组装或骨料。 这些聚集体的形成是在整个生物技术和生物制药行业中成功表达，纯化和储存的无处障碍。多域蛋白（例如天然和设计抗体以及其他主要β蛋白）的多域蛋白质尤其如此。 这些更复杂的蛋白质的预测设计受到对控制多域蛋白聚集的序列和结构的关键特征的局限性。该项目旨在提高对多域蛋白质聚集机制的基本理解，以便为工程师聚集的耐药性提供一般的设计规则，以抗治疗蛋白和其他生物技术产品。这是通过国家科学基金会的工业大学守门员计划，安进安进，杜兰大学和特拉华大学之间的合作伙伴关系。这项工作将集中于保留其已知功能（例如配体结合）的新抗体分子的计算设计，同时大大降低了它们的聚合速率，然后实验表征了聚集途径，以确保该设计预测在分子水平上正常工作。 从更广泛的角度来看，该项目着重于创建新的实验和计算工具，以更好地预测和控制，甚至消除蛋白质药物和其他生物技术产品中的聚集体。 这样做将降低工业科学家和工程师的开发成本，并减少上市时间以及与医疗应用中蛋白质聚集物相关的任何安全风险。 生物制药行业是美国就业市场增长最快，最有吸引力的行业之一，需要训练有素的劳动力，这将保持国际竞争力。 该项目的间接但同样重要的结果是培训下一代工业科学家和该行业的潜在领导者，以及开发新的教育工具，以在整个技术社区中更广泛地使用，并有可能直接用于在化学，生物化学，生物学和物理学等高中科学课程中直接使用。