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Updated: Mar 21, 2026

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks
Published on: November 25, 2015
Bioelectronic Interface Connecting Reversible Logic Gates Based on Enzyme and DNA Reactions
Nataliia Guz1, Tatiana A Fedotova2, Brian E Fratto1
1Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, 13699-5810, USA.
Abstract:
It is believed that connecting biomolecular computation elements in complex networks of communicating molecules may eventually lead to a biocomputer that can be used for diagnostics and/or the cure of physiological and genetic disorders. Here, a bioelectronic interface based on biomolecule-modified electrodes has been designed to bridge reversible enzymatic logic gates with reversible DNA-based logic gates. The enzyme-based Fredkin gate with three input and three output signals was connected to the DNA-based Feynman gate with two input and two output signals-both representing logically reversible computing elements. In the reversible Fredkin gate, the routing of two data signals between two output channels was controlled by the control signal (third channel). The two data output signals generated by the Fredkin gate were directed toward two electrochemical flow cells, responding to the output signals by releasing DNA molecules that serve as the input signals for the next Feynman logic gate based on the DNA reacting cascade, producing, in turn, two final output signals. The Feynman gate operated as the controlled NOT gate (CNOT), where one of the input channels controlled a NOT operation on another channel. Both logic gates represented a highly sophisticated combination of input-controlled signal-routing logic operations, resulting in redirecting chemical signals in different channels and performing orchestrated computing processes. The biomolecular reaction cascade responsible for the signal processing was realized by moving the solution from one reacting cell to another, including the reacting flow cells and electrochemical flow cells, which were organized in a specific network mimicking electronic computing circuitries. The designed system represents the first example of high complexity biocomputing processes integrating enzyme and DNA reactions and performing logically reversible signal processing.
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