颜林林
(2022-06-18 14:39):
#paper doi:10.1021/acssynbio.2c00120 ACS Synthetic Biology, 2022, Graph Computation Using Algorithmic Self-Assembly of DNA Molecules. 利用DNA等生物分子进行计算,可以追溯至上世纪90年代初,该领域这些年来不断进步并取得新成果,本文便是这样的一个案例。本文另辟蹊径,使用了一种称为DNA折纸的技术(即通过精巧地设计DNA序列,使其折叠成为某种特定形状),来解决一个“六顶点三色涂色”的图论计算问题。宏观上极少量的生物物质,其实包含着数量庞大的分子,因而,使用这些分子进行计算,是一个天然能提供巨大算力的策略,可以很轻松实现大量排列组合的暴力穷举,这就是生物计算概念提出的基本出发点之一。虽说被称为“DNA computing”,但它其实还远不及我们日常认识的通用电子计算机。本文的研究,是在特定图论问题上,人为列举出各个待求顶点的所有可能颜色,以及利用DNA链互补特性,设计相应序列,实现控制哪些顶点之间可以互相连接的规则。然后大量合成这样的分子,使其在特定实验条件下自由组合,最终利用AFM(原子力显微镜)扫描,找到符合特定结构形状的答案。由于使用了DNA折纸技术,AFM可以直接观察并识别出各顶点的“颜色”及连接组合,从而给出问题的求解。文章所解决的问题,被限定在特定范围,且只是概念验证阶段,未来要扩展到更多应用场景,使其具备“通用”或一定程度“通用”的程度,还有很长的路要走。
Graph Computation Using Algorithmic Self-Assembly of DNA Molecules
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Abstract:
DNA molecules have been used as novel computing tools, by which Synthetic DNA was designed to execute computing processes with a programmable sequence. Here, we proposed a parallel computing method using DNA origamis as agents to solve the three-color problem, an example of the graph problem. Each agent was fabricated with a DNA origami of ∼50 nm diameter and contained DNA probes with programmable sticky ends that execute preset computing processes. With the interaction of different nanoagents, DNA molecules self-assemble into spatial nanostructures, which embody the computation results of the three-color problem with polynomial numbers of computing nanoagents in a one-pot annealing step. The computing results were confirmed by atomic force microscopy. Our method is completely different from existing DNA computing methods in its computing algorithm, and it has an advantage in terms of computational complexity and results detection for solving graph problems.
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