CAREER: A Computational Design Approach for Predicting and Reengineering Plasticity and Selectivity in Protein-protein Interfaces

职业：预测和重新设计蛋白质-蛋白质界面的可塑性和选择性的计算设计方法

• 批准号: 0744541
• 负责人: Tanja Kortemme
• 金额: $ 71万
• 依托单位: University of California-San Francisco
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-01 至 2014-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0744541&HistoricalAwards=false
• 关键词: CAREER; Computational; Design; Approach; Predicting

The overall research objective of this CAREER project is to develop and assess improved computational modeling and design approaches focused on protein-protein interactions, to facilitate engineering of selective molecules to characterize, perform and control biological functions. In Aim 1, a model will be developed that will allow to optimize the fitness of a protein sequence for multiple selective criteria, such as binding to preferred partners while simultaneously avoiding unwanted interactions. In Aim 2, methods to more accurately model changes in protein conformation in response to binding events and designed mutations will be improved and evaluated. These models will be used to predict not only the optimal sequence, but also sets of tolerated sequences that capture the observed sequence, conformational and functional plasticity of protein-protein interactions. This research will build foundational approaches to quantitatively characterize plasticity and selectivity of protein interfaces. A practical outcome of this work will be a computational method to design sequence libraries and provide testable predictions for new proteins that are precise enough to have the desired function within complex biological environments.Computational methods developed under this project will be employed in teaching activities, integrating research and educational aims to introduce graduate, undergraduate and high-school students to structure-based biological engineering. As part of a new core graduate curriculum in Quantitative Biology, lecture-based, project-planning and hands-on practical course modules in protein biocomputing will be designed to teach a foundational understanding of current capabilities and limitations of modeling, and an appreciation of opportunities resulting from tight integration of theory and experiment. Project planning and practical units will emphasize multidisciplinary approaches allowing students with experimental and theoretical backgrounds to learn from each other. Undergraduate and high-school students will carry out summer projects in protein design and synthetic biology. New and improved computational methods will be disseminated broadly via the Rosetta package of computational tools that is available free-of-charge to academic users.

这一职业项目的总体研究目标是开发和评估以蛋白质-蛋白质相互作用为重点的改进的计算建模和设计方法，以促进对选择性分子的工程，以表征、执行和控制生物功能。在目标1中，将开发一个模型，该模型将允许优化蛋白质序列对多个选择标准的适合性，例如与首选伙伴的结合，同时避免不需要的相互作用。在目标2中，将改进和评估更准确地模拟蛋白质构象变化的方法，以响应结合事件和设计的突变。这些模型不仅将用于预测最优序列，而且还将用于预测捕捉到观察到的序列、蛋白质-蛋白质相互作用的构象和功能可塑性的可容忍序列集。这项研究将建立定量表征蛋白质界面可塑性和选择性的基础方法。这项工作的一个实际成果将是设计序列库的计算方法，并为新蛋白质提供可测试的预测，这些新蛋白质足够精确，可以在复杂的生物环境中具有所需的功能。在该项目下开发的计算方法将用于教学活动，将研究和教育目标结合起来，向研究生、本科生和高中生介绍基于结构的生物工程。作为数量生物学新的核心研究生课程的一部分，蛋白质生物计算的讲授、项目规划和动手实践课程模块将被设计来教授对当前建模能力和局限性的基础理解，以及对理论和实验紧密结合所产生的机会的欣赏。项目规划和实践单元将强调多学科方法，允许具有实验和理论背景的学生相互学习。本科生和高中生将开展蛋白质设计和合成生物学的暑期项目。新的和改进的计算方法将通过免费向学术用户提供的Rosetta计算工具包广泛传播。