Nanoscale computation is the recent advancement in the computing world to macro-scale systems, which developed techniques like DNA nanotechnology. In this line, DNA strand displacement (DSD) is a technique for implementing “nanoscale computations, including multi-layer logic circuits, catalytic amplification cycles, artificial neural networks, and distributed algorithms.” This paper presents a DSD systems modeling language using branches and loops as secondary structures.

The authors present examples--hairpin toehold exchange, branch migration leak, four-way branch migration, and three-way initiated four-way branch migration--that explain their programming implementation. They further emphasize that their first, second, and third examples are “the catalytic self-assembly of a three-arm branched junction,” the cross-catalytic signal amplification circuit, and the stochastic bipedal walker, respectively.

The authors use “1000 molecules of the initial tethered species (Species 1, purple) and 1200 molecules of the other initial species (Species 4, light blue)” to perform a stochastic simulation of the system. They also provide additional literature in four appendices, including an introduction to DSD, vectorized semantics, classic DSD semantics encoding, and a kappa comparison.

This paper is an interesting read for those who are working in the area of DSD and nanoscale computation involving “biofabrication, biosynthesis, and diagnostic and therapeutic applications,” according to the authors. They plan on involving complex technologies in the future to advance the dynamic nucleic acid systems designs in the Visual DSD software, which makes this paper worth reading.