Continuous variables logic via coupled automata using a DNAzyme cascade with feedback

• Published in: Chemical science (Cambridge) Vol. 8; no. 3; pp. 2161 - 2168
• Main Authors: Lilienthal, S, Klein, M, Orbach, R, Willner, I, Remacle, F, Levine, R D
• Format: Journal Article Web Resource
• Language: English
• Published: England Royal Society of Chemistry 01-03-2017
• Subjects: Boolean algebra; Cascades; Chemistry; Chimie; Continuity (mathematics); Continuous logic; DNAzymes; Feedback; Logic; Mathematical analysis; Mathematical models; Molecular Logic; Physical, chemical, mathematical & earth Sciences; Physique, chimie, mathématiques & sciences de la terre; Power series
• ISSN: 2041-6520; 2041-6539; 2041-6539
• DOI: 10.1039/c6sc03892a

The concentration of molecules can be changed by chemical reactions and thereby offer a continuous readout. Yet computer architecture is cast in textbooks in terms of binary valued, Boolean variables. To enable reactive chemical systems to compute we show how, using the Cox interpretation of probability theory, one can transcribe the equations of chemical kinetics as a sequence of coupled logic gates operating on continuous variables. It is discussed how the distinct chemical identity of a molecule allows us to create a common language for chemical kinetics and Boolean logic. Specifically, the logic AND operation is shown to be equivalent to a bimolecular process. The logic XOR operation represents chemical processes that take place concurrently. The values of the rate constants enter the logic scheme as inputs. By designing a reaction scheme with a feedback we endow the logic gates with a built in memory because their output then depends on the input and also on the present state of the system. Technically such a logic machine is an automaton. We report an experimental realization of three such coupled automata using a DNAzyme multilayer signaling cascade. A simple model verifies analytically that our experimental scheme provides an integrator generating a power series that is third order in time. The model identifies two parameters that govern the kinetics and shows how the initial concentrations of the substrates are the coefficients in the power series.