Increasing Redundancy Exponentially Reduces Error Rates during Algorithmic Self-Assembly

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• 作者：Rebecca Schulman ; Christina Wright ; Erik Winfree
• 刊名：ACS Nano
• 出版年：2015
• 出版时间：June 23, 2015
• 年：2015
• 卷：9
• 期：6
• 页码：5760-5771
• 全文大小：776K
• ISSN：1936-086X

文摘

While biology demonstrates that molecules can reliably transfer information and compute, design principles for implementing complex molecular computations in vitro are still being developed. In electronic computers, large-scale computation is made possible by redundancy, which allows errors to be detected and corrected. Increasing the amount of redundancy can exponentially reduce errors. Here, we use algorithmic self-assembly, a generalization of crystal growth in which the self-assembly process executes a program for growing an object, to examine experimentally whether redundancy can analogously reduce the rate at which errors occur during molecular self-assembly. We designed DNA double-crossover molecules to algorithmically self-assemble ribbon crystals that repeatedly copy a short bitstring, and we measured the error rate when each bit is encoded by 1 molecule, or redundantly encoded by 2, 3, or 4 molecules. Under our experimental conditions, each additional level of redundancy decreases the bitwise error rate by a factor of roughly 3, with the 4-redundant encoding yielding an error rate less than 0.1%. While theory and simulation predict that larger improvements in error rates are possible, our results already suggest that by using sufficient redundancy it may be possible to algorithmically self-assemble micrometer-sized objects with programmable, nanometer-scale features.