AF: SHF: Small: Algorithmic and Architectural Foundation for Next-Generation Collective DNA Robots

AF：SHF：小型：下一代集体 DNA 机器人的算法和架构基础

• 批准号: 1813550
• 负责人: Lulu Qian
• 金额: $ 42.5万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1813550&HistoricalAwards=false
• 关键词: AF; SHF; Small; Algorithmic; Architectural

A molecular robot is an important type of artificial molecular machine that automatically carry out nanomechanical tasks. DNA is an excellent material for building molecular robots, because their geometric, thermodynamic and kinetic properties are well understood and highly programmable. There exist no systematic approaches for translating high-level mechanical tasks to low-level molecular implementations nor software tools that enable researchers with diverse backgrounds to build DNA robots with new functions. To accomplish that, more simple algorithms and more modular building blocks are needed to create a wider range of collective behaviors, until there is enough understanding for the development of a molecular robotics programming language that will work in practice. This project will provide better answers to the following questions: To what extent can simple algorithms allow increasingly complex nanomechanical tasks to be programmed and carried out by DNA molecules? Does cooperation in DNA robots allow more complex tasks to be accomplished with less time and less energy? What composability issues arise when new building blocks are added to the toolbox for general-purpose DNA robots? What design principles can allow DNA robots to function well in increasingly complex and diverse operating environments? The scientific understanding will be incorporate into public online software tools to assist the design and construction of molecular robots, which will be introduced into the classroom. Course materials will be shared among multiple educational institutions. Public engagement will be promoted through public talks, lab tours, podcasts, news stories, YouTube videos and artwork.The project involves three main goals: developing a new building block for leaving pheromone-like signals to mark where a robot has been, demonstrating how the new building block can be used to construct DNA robots that find and modify a direct path from the entrance to the exit in an arbitrary maze, and developing software tools that automatically convert user-specified robotics systems to design diagrams, simulations, DNA sequences and experimental protocols. DNA origami technique will be used to build testing grounds for DNA robots, while DNA strand displacement mechanism will be used to program the behavior of DNA robots. Fluorescence spectroscopy and atomic force microscopy will be used to quantitatively analyze the behavior of DNA robots, in bulk and at the single-molecule level. The team of investigators will study the mechanisms for tuning the behavior of DNA robots, if it is qualitatively but not quantitatively as designed, and understand how the behavior of DNA robots depends on the specific configuration of their operating environment. The new building block expands the toolbox for general-purpose DNA robots and allows tasks that involve surveying and marking an unknown environment. The maze-solving robots could be used to perform efficient molecular transportation where a group of leader robots mark a direct path in a complex environment using very little energy and a group of follower robots walk on marked path only to transport molecular cargos without spending any time on indirect routes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

分子机器人是一种重要的人工分子机器，可以自动执行纳米机械任务。DNA是构建分子机器人的绝佳材料，因为它们的几何、热力学和动力学性质已被很好地理解，且高度可编程。目前还没有系统的方法将高层次的机械任务转化为低层次的分子实现，也没有软件工具使具有不同背景的研究人员能够构建具有新功能的DNA机器人。为了实现这一目标，需要更简单的算法和更多的模块化构建块来创建更广泛的集体行为，直到有足够的理解来开发一种在实践中有效的分子机器人编程语言。该项目将为以下问题提供更好的答案：简单的算法在多大程度上可以允许DNA分子编程和执行日益复杂的纳米机械任务？DNA机器人中的合作是否可以让更复杂的任务以更少的时间和更少的精力完成？当通用DNA机器人的工具箱中添加新的构建块时，会出现什么可组合性问题？什么样的设计原则可以让DNA机器人在日益复杂和多样化的操作环境中正常工作？科学的理解将被纳入公共在线软件工具，以帮助分子机器人的设计和建造，这将被引入课堂。课程材料将在多个教育机构之间共享。公众参与将通过公开讲座、实验室图尔斯参观、播客、新闻报道、YouTube视频和艺术品来促进。该项目包括三个主要目标：开发一种新的构建块，用于留下信息素样信号来标记机器人去过的地方，演示如何使用新的构建块来构建DNA机器人，这些机器人可以在任意迷宫中找到并修改从入口到出口的直接路径，开发软件工具，自动将用户指定的机器人系统转换为设计图，模拟，DNA序列和实验协议。DNA折纸技术将被用于构建DNA机器人的试验场，而DNA链置换机制将被用于编程DNA机器人的行为。荧光光谱和原子力显微镜将用于定量分析DNA机器人的行为，在散装和单分子水平。研究人员将研究调整DNA机器人行为的机制，如果它是定性的，而不是定量的设计，并了解DNA机器人的行为如何取决于其操作环境的特定配置。新的构建模块扩展了通用DNA机器人的工具箱，并允许执行涉及测量和标记未知环境的任务。迷宫-求解机器人可用于执行有效的分子运输，其中一组领导机器人在复杂环境中使用非常少的能量标记一条直接路径，一组跟随机器人仅在标记的路径上行走以运输分子货物，而不花费任何时间在间接路径上。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值进行评估而被认为值得支持和更广泛的影响审查标准。

项目成果

Programming and simulating chemical reaction networks on a surface

• DOI: 10.1098/rsif.2019.0790
• 发表时间: 2020-05-27
• 期刊: JOURNAL OF THE ROYAL SOCIETY INTERFACE
• 影响因子: 3.9
• 作者: Clamons, Samuel;Qian, Lulu;Winfree, Erik
• 通讯作者: Winfree, Erik