ABI Innovation: Robotics-inspired modeling & design of proteins

这项研究将允许研究人员使用软件工具设计具有新功能的蛋白质，以提高生产过程的成功率。通过测试和改进设计步骤，它还将使研究人员和工程师能够生产出功能比以前更复杂的蛋白质：这些新活动在推进基础研究和生物技术方面具有巨大潜力。蛋白质在细胞和技术环境中发挥着大量复杂而重要的功能：它们可以将化学反应速度加快数百倍，它们负责细胞之间的交流，它们是构建细胞结构和组织的基本材料。设计蛋白质而不是使用已知的蛋白质的优势包括：能够修改副产品的成分，从而减少对环境的破坏；制造可以实时探测活细胞活动的低毒传感器；以及创造独特的材料，在纳米尺度上形成定义的结构。为了确保这些方法被广泛使用，所有经过批准的计算方法都将通过Rosetta软件套件以源代码的形式提供。该软件对学术用户免费，通常由生物技术和制药公司授权。在这项资助下开发的新方法也将用于课堂上的团队项目和跨学科研究活动，强调学生在生物和物理/工程科学方面的合作。这项研究旨在解决计算蛋白质设计中的一个主要障碍：缺乏足够准确地预测序列和结构变化的计算方法。设计方法改变了蛋白质序列，但在绝大多数情况下，只允许进行最小的结构调整。然而，当前方法没有捕捉到的构象变化是规则，而不是例外，也是失败设计的主要原因。此外，可能需要新的构象来设计新的功能，例如重塑现有的功能位点以适应不同的结合伙伴。最后，许多蛋白质经历功能构象变化，例如分子开关或酶和蛋白质机器在构象状态之间循环；这种复杂的活动目前还无法设计。目标1寻求推进蛋白质结构变化的建模方法，并解决在产生相关蛋白质构象和区分正确与错误预测方面的挑战；将使用已建立的和新的基准来评估局限性和量化改进。目标2将开发一种方法来设计新的功能，这些功能需要蛋白质构象的实质性变化。该方法将通过试验性的正向工程应用进行测试。AIM 3将为经过测试的方法提供“协议捕获”文件，并在寻求扩大参与的教育和研究活动中利用已开发的方法。经过验证的方法将作为源代码通过https://www.rosettacommons.org.提供

This research will permit researchers to design proteins that have new functions, using software tools that improve the success of the production process. By testing and improving the design steps it will also allow researchers and engineers to produce proteins that have functions more complex than could be made before: these new activities have enormous potential to advance basic research and biotechnology. Proteins perform a vast array of complex and important functions in cells and in technology settings: they can speed up the rate of chemical reactions by several hundred fold, they are responsible for how cells communicate, and they are the basic material for building cell structures and tissues. The advantages to designing proteins instead of using those already known include being able to modify what by-products are made so that there is less damage to the environment, make low-toxicity sensors that can probe the action of living cells in real time, and create unique materials that form defined structures at the nanoscale. To ensure the methods are widely available, all approved computational methods will be available as source code via the Rosetta software suite. This software is free of charge for academic users, and is commonly licensed by biotechnology and pharmaceutical companies. The new methods developed under this grant will also be used in classrooms for team-based projects and for interdisciplinary research activities that emphasize collaboration between students in the biological and physical/engineering sciences.This research aims to address a principal barrier in computational protein design: the lack of computational approaches that predict both sequence and structural changes with sufficient accuracy. Design methods change the protein sequence but in the vast majority of cases allow only minimal structural adjustments. Yet conformational changes not captured by current methods are the rule rather than the exception, and a main reason for failed designs. Moreover, new conformations might be required to engineer new functions, e.g. to reshape an existing functional site to accommodate a different binding partner. Finally, many proteins undergo functional conformational changes, such as molecular switches or enzymes and protein machines that cycle between conformational states; such complex activities are currently not designable. Aim 1 seeks to advance methods to model changes in protein structure, and address challenges in both generating relevant protein conformations and distinguishing correct from incorrect predictions; established and new benchmarks will be used to assess limitations and quantify improvements. Aim 2 will develop an approach to design new functions that require substantial changes in protein conformation. The approach will be tested by experimental forward-engineering applications. Aim 3 will provide "protocol capture" documentation for tested methods and utilize developed methods in educational and research activities that seek to broaden participation. Validated methods will be available as source code viahttps://www.rosettacommons.org.