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

该CAREER项目的总体研究目标是开发和评估专注于蛋白质-蛋白质相互作用的改进的计算建模和设计方法，以促进选择性分子的工程化，以表征，执行和控制生物功能。在目标1中，将开发一种模型，该模型将允许针对多个选择标准优化蛋白质序列的适应性，例如与优选的伴侣结合，同时避免不必要的相互作用。在目标2中，将改进和评估更准确地模拟蛋白质构象响应于结合事件和设计突变的变化的方法。这些模型将被用来预测不仅是最佳的序列，但也组的耐受序列，捕获观察到的序列，构象和功能可塑性的蛋白质-蛋白质相互作用。这项研究将建立基础的方法来定量表征蛋白质界面的可塑性和选择性。本研究的成果将是设计序列库的计算方法，并对在复杂的生物环境中具有所需功能的新蛋白质提供可测试的预测。本研究项目开发的计算方法将用于教学活动，将研究和教育目的结合起来，向研究生，本科生和高中生介绍基于结构的生物工程。作为定量生物学新核心研究生课程的一部分，蛋白质生物计算中基于讲座、项目规划和动手实践的课程模块将被设计用于教授对建模当前能力和局限性的基本了解，以及对理论和实验紧密结合所带来的机会的认识。项目规划和实践单位将强调多学科的方法，让学生与实验和理论背景，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Rosetta计算工具包广泛传播，该工具包免费提供给学术用户。

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.