Quantifying molecular and cellular constraints on protein function through in vivo fitness assays and computational protein design

蛋白质促进了生物学中几乎所有有用的功能，并且在设计蛋白质以执行全新功能方面存在巨大的潜力。这些新功能可能在工业中很有用，可以制造一种新的化学品，或者在医疗保健或环境中很有用。然而，目前许多功能过于复杂，无法用现有的预测方法进行设计。该项目旨在通过推进计算模型来解决一个主要的瓶颈，包括蛋白质的多种功能状态。然后，该项目将利用这些多状态模型，为蛋白质在分子水平和活细胞的复杂环境中如何发挥作用的设计原则提供基本见解。更广泛地说，由此产生的新方法和知识将推动有用的新蛋白质的学术和工业设计，如生物催化剂，用于成本效益高和对环境负责的制造。开发的计算方法将集成到蛋白质设计软件套件Rosetta中，该软件作为源代码免费提供给大量学术用户，并由几家生物技术和制药公司授权。新的设计方法将被纳入研究生水平的课程，并将被纳入研究和推广活动，重点是来自社会经济弱势背景的学生、代表性不足的群体和计算科学领域的女性。设计具有自然界不存在的功能的蛋白质的能力的进展受到对蛋白质功能的关键限制的不完整理解的限制，这些限制需要通过预测模型来捕获。为了推进蛋白质的建模和设计，本项目的目标是确定蛋白质功能的分子和细胞约束，并将这些知识纳入改进的计算方法中，以设计多种功能约束下的蛋白质。该项目将首先建立一个实验系统，允许对序列变化对功能的影响进行全面检查，并能够通过计算预测这些影响。实验将使用深度突变扫描和体内分析来询问代谢酶二氢叶酸还原酶，这将确定数千种变体在不同背景下的适应性影响是如何变化的，这些背景会扰乱分子功能和细胞环境。其次，该项目旨在推进计算蛋白质设计方法，以模拟多种约束下的蛋白质序列。通过与实验的比较对模型进行的测试将指导急需的改进，并将确定多状态模型未捕获的细胞约束。由此产生的知识将导致改进的计算方法，通过考虑多种功能约束来建模和设计蛋白质，这些约束可以应用于工程中新的和有用的蛋白质功能的重要挑战。该奖项由分子和细胞生物科学部的系统和合成生物学项目、分子生物物理学项目以及化学部的生命过程化学项目提供支持。

Proteins facilitate nearly every useful function in biology, and there is enormous potential in designing proteins to perform completely new functions. These new functions might be useful in industry, enabling the manufacture of a new chemical, or in health care or the environment. However, many functions are currently too complex to design by current predictive methods. This project seeks to address a major bottleneck by advancing computational models to include multiple functional states of the protein. The project will then utilize these multi-state models to provide fundamental insights into design principles of how proteins function both at the molecular level and in the complex environment of living cells. More broadly, the resulting new methods and knowledge will advance academic and industrial design of useful new proteins such as biocatalysts for cost-effective and environmentally responsible manufacturing. The developed computational methods will be integrated into the protein design software suite Rosetta, which is available freely as source code to a large community of academic users, and is licensed by several biotechnological and pharmaceutical companies. New design methods will be integrated into graduate-level courses, and will be incorporated in research and outreach activities focused on students from socioeconomically disadvantaged backgrounds, underrepresented groups, and women in computational sciences.Progress in the ability to design proteins with functions not existing in nature has been limited by an incomplete understanding of the key constraints on protein function that need to be captured by a predictive model. To advance modeling and design of proteins, the objectives of this project are to determine molecular and cellular constraints on protein function, and to incorporate this knowledge into improved computational methods to design proteins under multiple functional constraints. This project will first establish an experimental system that allows for a comprehensive examination of the effect of sequence changes on function, and the ability to predict these effects computationally. Experiments will interrogate the metabolic enzyme dihydrofolate reductase using deep mutational scanning and in vivo assays that will determine how fitness effects of thousands of variants change in different backgrounds that perturb molecular function and cellular context. Second, the project seeks to advance computational protein design methods to model protein sequences under multiple constraints. Tests of the model by comparison to experiments will guide critically needed improvements and will identify cellular constraints not captured by the multi-state model. The resulting knowledge will lead to improved computational methods to model and design proteins by considering multiple functional constraints that can be applied to important challenges in engineering new and useful protein functions.This award is supported by the Systems and Synthetic Biology Program and the Molecular Biophysics Program in the Division of Molecular and Cellular Biosciences, and the Chemistry of Life Processes Program in the Division of Chemistry.