Rectangular DNA structure allows for one-dimensional random walk functionality

In recent years, the biomolecule DNA has been looked to for efficient molecular computing. While many DNA lattices have been constructed that can provide nanoscale resolution for tasks including copying and binary counting, unpredictable random walk patterns remain elusive. One new study has shown a path forward for such functionality in DNA-based computing.

Raza et al. have demonstrated the construction of one-dimensional unbiased random walk lattices using algorithmic DNA self-assembly. Using a rectangular double-crossover DNA molecule with four strands and four sticky ends as its rule tile, the group’s approach yields molecules that are capable of randomly choosing between left or right movement.

“Although random walk model is a well-established model, it has not been used to design DNA building blocks, which contain a rule of random walk, owing to the difficulty in implementing unbiased directional information on sticky-ends,” said author Sung Ha Park. “We believe that our work is first demonstration of one-dimensional random walk patterns formed on DNA lattices experimentally.”

The hairpin-embedded rule tiles possessed the same sticky-end base sequences input domains, which allowed the molecule to give equal opportunity of delivering information to either the left or the right in each succeeding layer.

Using atomic force microscopy, the group analyzed metrics of the molecules to find that the behavior of average displacement and mean-square displacement agreed with theoretically expected results for random walk behavior and diffusion law, respectively.

Park hopes the group’s findings lead to further advances in molecular, DNA-based computing and looks to continue to make steps toward experimentally constructing such a computer in the future.

Source: “Construction of one-dimensional random walk lattices using DNA algorithmic self-assembly,” by Muhammad Tayyab Raza, Anshula Tandon, Junyoung Son, Suyoun Park, Sungjin Lee, Hyunjae Cho, Tai Hwan Ha, and Sung Ha Park, AIP Advances (2020). The article can be accessed at https://doi.org/10.1063/1.5121827 .