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1. Simplifying Chemical Reaction Network Implementations with Two-Stranded DNA Building Blocks

   https://doi.org/10.4230/LIPIcs.DNA.2020.2  

   Johnson, Robert F; Qian, Lulu (September 2020, Leibniz international proceedings in informatics)

   In molecular programming, the Chemical Reaction Network model is often used to describe real or hypothetical systems. Often, an interesting computational task can be done with a known hypothetical Chemical Reaction Network, but often such networks have no known physical implementation. One of the important breakthroughs in the field was that any Chemical Reaction Network can be physically implemented, approximately, using DNA strand displacement mechanisms. This allows us to treat the Chemical Reaction Network model as a programming language and the implementation schemes as its compiler. This also suggests that it would be useful to optimize the result of such a compilation, and in general to find effective ways to design better DNA strand displacement systems. We discuss DNA strand displacement systems in terms of "motifs", short sequences of elementary DNA strand displacement reactions. We argue that describing such motifs in terms of their inputs and outputs, then building larger systems out of the abstracted motifs, can be an efficient way of designing DNA strand displacement systems. We discuss four previously studied motifs in this abstracted way, and present a new motif based on cooperative 4-way strand exchange. We then show how Chemical Reaction Network implementations can be built out of abstracted motifs, discussing existing implementations as well as presenting two new implementations based on 4-way strand exchange, one of which uses the new cooperative motif. The new implementations both have two desirable properties not found in existing implementations, namely both use only at most 2-stranded DNA complexes for signal and fuel complexes and both are physically reversible. There are reasons to believe that those properties may make them more robust and energy-efficient, but at the expense of using more fuel complexes than existing implementation schemes. 

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2. Controlling DNA–RNA strand displacement kinetics with base distribution

   https://doi.org/10.1073/pnas.2416988122  

   Ratajczyk, Eryk J; Bath, Jonathan; Sulc, Petr; Doye, Jonathan; Louis, Ard A; Turberfield, Andrew J (June 2025, Proceedings of the National Academy of Sciences)

   DNA–RNA hybrid strand displacement underpins the function of many natural and engineered systems. Understanding and controlling factors affecting DNA–RNA strand displacement reactions is necessary to enable control of processes such as CRISPR-Cas9 gene editing. By combining multiscale modeling with strand displacement experiments, we show that the distribution of bases within the displacement domain has a very strong effect on reaction kinetics, a feature unique to DNA–RNA hybrid strand displacement. Merely by redistributing bases within a displacement domain of fixed base composition, we are able to design sequences whose reaction rates span more than four orders of magnitude. We extensively characterize this effect in reactions involving the invasion of dsDNA by an RNA strand, as well as the invasion of a hybrid duplex by a DNA strand. In all-DNA strand displacement reactions, we find a predictable but relatively weak sequence dependence, confirming that DNA–RNA strand displacement permits far more thermodynamic and kinetic control than its all-DNA counterpart. We show that oxNA, a recently introduced coarse-grained model of DNA–RNA hybrids, can reproduce trends in experimentally observed reaction rates. We also develop a simple kinetic model for predicting strand displacement rates. On the basis of these results, we argue that base distribution effects may play an important role in natural R-loop formation and in the function of the guide RNAs that direct CRISPR-Cas systems. 

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3. Geometric Enumeration of Localized DNA Strand Displacement Reaction Networks

   https://doi.org/10.4230/LIPIcs.DNA.30.1  

   Lakin, Matthew R; Kumar, Sarika (January 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Seki, Shinnosuke; Stewart, Jaimie Marie (Ed.)

   Localized molecular devices are a powerful tool for engineering complex information-processing circuits and molecular robots. Their practical advantages include speed and scalability of interactions between components tethered near to each other on an underlying nanostructure, and the ability to restrict interactions between more distant components. The latter is a critical feature that must be factored into computational tools for the design and simulation of localized molecular devices: unlike in solution-phase systems, the geometries of molecular interactions must be accounted for when attempting to determine the network of possible reactions in a tethered molecular system. This work aims to address that challenge by integrating, for the first time, automated approaches to analysis of molecular geometry with reaction enumeration algorithms for DNA strand displacement reaction networks that can be applied to tethered molecular systems. By adapting a simple approach to solving the biophysical constraints inherent in molecular interactions to be applicable to tethered systems, we produce a localized reaction enumeration system that enhances previous approaches to reaction enumeration in tethered system by not requiring users to explicitly specify the subsets of components that are capable of interacting. This greatly simplifies the user’s task and could also be used as the basis of future systems for automated placement or routing of signal-transmission and logical processing in molecular devices. We apply this system to several published example systems from the literature, including both tethered molecular logic systems and molecular robots. 

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4. Parallel molecular computation on digital data stored in DNA

   https://doi.org/10.1073/pnas.2217330120  

   Wang, Boya; Wang, Siyuan Stella; Chalk, Cameron; Ellington, Andrew D; Soloveichik, David (September 2023, Proceedings of the National Academy of Sciences)

   DNA is an incredibly dense storage medium for digital data. However, computing on the stored information is expensive and slow, requiring rounds of sequencing, in silico computation, and DNA synthesis. Prior work on accessing and modifying data using DNA hybridization or enzymatic reactions had limited computation capabilities. Inspired by the computational power of “DNA strand displacement,” we augment DNA storage with “in-memory” molecular computation using strand displacement reactions to algorithmically modify data in a parallel manner. We show programs for binary counting and Turing universal cellular automaton Rule 110, the latter of which is, in principle, capable of implementing any computer algorithm. Information is stored in the nicks of DNA, and a secondary sequence-level encoding allows high-throughput sequencing-based readout. We conducted multiple rounds of computation on 4-bit data registers, as well as random access of data (selective access and erasure). We demonstrate that large strand displacement cascades with 244 distinct strand exchanges (sequential and in parallel) can use naturally occurring DNA sequence from M13 bacteriophage without stringent sequence design, which has the potential to improve the scale of computation and decrease cost. Our work merges DNA storage and DNA computing, setting the foundation of entirely molecular algorithms for parallel manipulation of digital information preserved in DNA.< 

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5. A geometric framework for reaction enumeration in computational nucleic acid devices

   https://doi.org/10.1098/rsif.2023.0259  

   Kumar, Sarika; Lakin, Matthew R (November 2023, Journal of The Royal Society Interface)

   Cascades of DNA strand displacement reactions enable the design of potentially large circuits with complex behaviour. Computational modelling of such systems is desirable to enable rapid design and analysis. In previous work, the expressive power of graph theory was used to enumerate reactions implementing strand displacement across a wide range of complex structures. However, coping with the rich variety of possible graph-based structures required enumeration rules with complicated side-conditions. This paper presents an alternative approach to tackle the problem of enumerating reactions at domain level involving complex structures by integrating with a geometric constraint solving algorithm. The rule sets from previous work are simplified by replacing side-conditions with a general check on the geometric plausibility of structures generated by the enumeration algorithm. This produces a highly general geometric framework for reaction enumeration. Here, we instantiate this framework to solve geometric constraints by a structure sampling approach in which we randomly generate sets of coordinates and check whether they satisfy all the constraints. We demonstrate this system by applying it to examples from the literature where molecular geometry plays an important role, including DNA hairpin and remote toehold reactions. This work therefore enables integration of reaction enumeration and structural modelling. 

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