Dokholyan Nikolay V
Departments of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA.
Departments of Biochemistry & Molecular Biology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA.
NPJ Syst Biol Appl. 2021 Mar 11;7(1):15. doi: 10.1038/s41540-021-00176-8.
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 logic gates. Combining these operands into a set of operations will result in a functional program, which is executed using nanoscale computing agents (NCAs). These agents would respond to any given input and return the desired output signal. 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 the development of in situ precision therapeutics. Since NCAs can be extended to novel reactions and processes not seen in biological systems, the growth of this field will spark the growth of biotechnological applications with wide-ranging impacts, including fields not typically considered relevant to biology. Unlike traditional approaches in synthetic biology that are based on the rewiring of signaling pathways in cells, NCAs are autonomous vehicles based on single-chain proteins. In this perspective, I will introduce and discuss this new field of biological computing, as well as challenges and the future of the NCA. Addressing these challenges will provide a significant leap in technology for programming living cells.
近年来蛋白质设计的出现，使我们能够开发一种“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。将这些操作数组合成一组操作将产生一个功能程序，该程序使用纳米级计算代理（NCA）来执行。这些代理将响应任何给定输入并返回所需的输出信号。利用自然进化过程的能力将使代码在计算过程中“进化”，从而实现全新的算法开发。NCA将彻底改变生物系统的研究，使人们对人类生物学和疾病有更深入的了解，并促进原位精准治疗的发展。由于NCA可以扩展到生物系统中未见过的新反应和过程，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，包括一些通常不被认为与生物学相关的领域。与基于细胞信号通路重新布线的合成生物学传统方法不同，NCA是基于单链蛋白质的自主载体。在这篇综述中，我将介绍和讨论这个生物计算新领域，以及NCA面临的挑战和未来。应对这些挑战将为对活细胞进行编程的技术带来重大飞跃。
