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Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming
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 pr...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952909/ https://www.ncbi.nlm.nih.gov/pubmed/33707429 http://dx.doi.org/10.1038/s41540-021-00176-8 |
Sumario: | 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. |
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