Nanoscale programing of cellular and physiological phenotypes

摘要 近年来蛋白质设计的出现使我们有能力开发“纳米级” 编程语言”，其中分子作为操作数，其构象状态充当 逻辑门。通过蛋白质将这些操作数组合成更大的分子和分子复合物 工程将使我们能够使用纳米级计算代理（NCA）编写和执行“代码”。这些代理 将响应任何给定的输入并返回所需的输出信号。虽然“计算”的速度会 比无机硅基计算机慢得多，一个单元可以包含比无机硅计算机更多的 NCA 当前存在的任何超级计算机中的 CPU 数量。利用自然进化的能力 进程将允许代码在计算过程中“进化”，从而实现全新的算法 事态发展。 NCA 将彻底改变生物系统的研究，使人们能够更深入地了解 人类生物学和疾病，并促进原位精准疗法的发展。由于 NCA 可以 扩展到生物系统中未见的新反应和过程，该领域的发展将激发 具有广泛影响的生物技术应用的增长，包括通常不考虑的领域 与生物学相关。与基于信号重新布线的合成生物学传统方法不同 NCA 是基于单链蛋白的自主车辆。 NCA 提供正交 以及控制细胞表型的补充手段。 12年来，我们集团不断发展 为此目的，通过工程改造可以由光和小分子控制的蛋白质。我们 设计的功能原型已经在细胞运动领域提供了宝贵的见解。在这里，我们 计划 (i) 进一步扩大 NCA 输入的范围，(ii) 将其他生物分子（例如 RNA）纳入 我们的 NCA 库，以及 (iii) 扩展在纳米级“编写”算法的方法组合。的 该提案的主要目标是：（1）扩大蛋白质调节的输入范围。我们计划 利用/设计通过构象变化响应 pH 和温度的蛋白质，以调节 目标蛋白的活性。 (2) 扩展我们的方法来建模和调节 RNA 分子。没有工具 目前存在用于小分子与 RNA 结合的计算评估（对接问题）。造型 由于骨架的灵活性，RNA 的结构和动力学具有挑战性。我们计划开发一个平台 解决RNA结构和小分子对接问题。 (3)开发合理设计的工具 蛋白质中的变构网络。 “重新连接”蛋白质变构网络的技术尚不存在。 利用我们的映射变构方法，我们计划构建一种搜索算法，该算法将迭代地重新布线 远端蛋白质位点之间的通讯途径。应对这些挑战将提供重要的 活细胞编程技术的飞跃。虽然本提案中概述的研究方向是 雄心勃勃，我们和其他人已经为这项技术的可行性和触手可及奠定了基础。

ABSTRACT The advent of protein design in recent years has brought us within reach of developing a “nanoscale programing language,” in which molecules serve as operands with their conformational states functioning as logical gates. Combining these operands into larger molecules and molecular complexes through protein engineering will allow us to write and execute “code” using nanoscale computing agents (NCAs). These agents would respond to any given input and return a desired output signal. While the speed of the “computation” will be significantly slower than that of inorganic silicon-based computers, one cell can contain more NCAs than the number of CPUs in any supercomputer currently in existence. The ability to utilize natural evolutionary processes would allow code to “evolve” in the course of computation, thus enabling radically new algorithmic developments. NCAs will revolutionize the studies of biological systems, enable a deeper understanding of human biology and disease, and facilitate development of in situ precision therapeutics. Since NCAs can be extended to novel reactions and processes not seen in biological systems, growth of this field will spark the growth of biotechnological applications with wide-ranging impact, including to fields not typically considered relevant to biology. Unlike traditional approaches in synthetic biology that are based on rewiring of signaling pathways in cells, NCAs are autonomous vehicles based on single chain proteins. NCAs offer an orthogonal and complementary means for controlling cellular phenotypes. In the past 12 years, our group has developed technology toward this end, by engineering proteins that can be controlled by light and small molecules. We designed functional prototypes that have already offered valuable insights in the cellular motility field. Here, we plan to (i) further expand the repertoire of NCA inputs, (ii) include other biological molecules, such as RNA, in our library of NCAs, and (iii) expand the portfolio of methods for “writing” algorithms at the nanoscale level. The main objectives of this proposal are: (1) Extend the repertoire of inputs for regulation of proteins. We plan to utilize/design proteins that respond to pH and temperature via conformational change in order to modulate the activities of target proteins. (2) Extend our approaches to model and regulate RNA molecules. No tools currently exist for computational evaluation of small molecule binding to RNA (the docking problem). Modeling the structure and dynamics of RNA is challenging due to backbone flexibility. We plan to develop a platform to address both the RNA structure and small molecule docking problems. (3) Develop tools to rationally design allosteric networks in proteins. The technology to “rewire” allosteric networks in proteins does not exist yet. Capitalizing on our method for mapping allostery, we plan to build a search algorithm that will iteratively rewire communication pathways between distal protein sites. Addressing these challenges will provide a significant leap in technology for programming living cells. While the research directions outlined in this proposal are ambitious, we and others have created the basis for this technology to be feasible and within reach.