Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming

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 logic gates. Combining these operands into a set of operations will result in a func...

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Main Author: Nikolay V. Dokholyan
Format: Article
Language:English
Published: Nature Publishing Group 2021-03-01
Series:npj Systems Biology and Applications
Online Access:https://doi.org/10.1038/s41540-021-00176-8
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spelling doaj-895cd58474fa4e2ebf5e9c2cd59de2b92021-03-11T12:46:10ZengNature Publishing Groupnpj Systems Biology and Applications2056-71892021-03-01711510.1038/s41540-021-00176-8Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programmingNikolay V. Dokholyan0Departments of Pharmacology, Penn State College of MedicineAbstract 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.https://doi.org/10.1038/s41540-021-00176-8
collection DOAJ
language English
format Article
sources DOAJ
author Nikolay V. Dokholyan
spellingShingle Nikolay V. Dokholyan
Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
npj Systems Biology and Applications
author_facet Nikolay V. Dokholyan
author_sort Nikolay V. Dokholyan
title Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
title_short Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
title_full Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
title_fullStr Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
title_full_unstemmed Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
title_sort nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
publisher Nature Publishing Group
series npj Systems Biology and Applications
issn 2056-7189
publishDate 2021-03-01
description 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 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.
url https://doi.org/10.1038/s41540-021-00176-8
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