DNA- and RNA-Based Computing Systems. Группа авторов
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Figure 3.2 State graph with state transition implemented by CRNs.
Source: Adapted from Murphy et al. [13].
To show the capability of DNA materials to establish computers, many researchers begin with building Turing machines. Apart from the aforementioned simulations of Turing machines in Figure 3.1 [1], there is a universal molecular Turing machine based on site‐directed mutagenesis [15]. Qian et al. employ a “history‐free” method to implement CRNs, based on which the authors implement irreversible and reversible stack machines [16]. Besides the attempts to build Turing machines, some researchers start from the design of DNA strand displacement reactions and propose instruction sets for DNA computers. The work called SIMD||DNA (Single Instruction Multiple Data DNA) [10] leverages the cascade of DNA strand displacement reactions. By introducing a set of binary encoding rules that utilize different arrangements of upper DNA strands of DNA complexes to represent “1” and “0,” data can be stored in DNA “registers” (multistranded complexes). When adding auxiliary single DNA strands that equal to executing instructions, the upper single DNA strands can be attached/displaced/detached from the DNA complexes, hence changing the encoded data stored in DNA “registers.” An example of Rule 110 Automata is shown in Figure 3.3.
Figure 3.3 Implementation of Rule 110 Automata. Two different arrangements of upper single DNA strands within each cell (slices of DNA complex separated by dashed lines) represent “1” and “0,” respectively. When executing an instruction, some specific DNA strands are added to the system to initiate the attachment, detachment, and displacement of upper DNA strands. The combination of such instructions changes the state of related cells, resulting in state transitions of the automata after the execution of all instructions.
Source: Modified from Wang et al. [10].
With the computing power of CRNs, one critical issue is how to implement such formal reactions in the real world using DNA reactions. Soloveichik et al. propose a DNA reaction substrate in [6], based on which theoretically designed reactions with less than three reactants can be readily mapped to DNA strand displacement reactions. The kinetic features of original formal reactions are approximately retained, as proved by mass action kinetic analysis. For bimolecular reactions, Qian et al. propose a design of DNA strand displacement reactions [16] to map such formal reactions. The model can address both reversible and irreversible formal reactions; unimolecular reactions and reactions with higher orders can be similarly constructed. Experimental work [7], which shows that bimolecular reactions can be mapped to DNA strand displacement reaction cascade, is based on a similar mechanism. Fluorophore experiments prove that the cascaded DNA reactions overall simulate the initial formal reactions. The diagrams of such mapping models are provided in Figure 3.4.
Figure 3.4 Diagrams of the DNA implementation models. (a) Mapping model of bimolecular reactions in [6]. The two reactants are taken into the system using the first two reactions: one reversible and one irreversible, and the third irreversible reaction displaces the products of the formal reaction.
Source: Modified from Soloveichik et al. [6].
(b) Reaction design of A + B → C. By cascading several displacement reactions, the output is eventually displaced, and kinetic features are well reserved.
Source: Adapted from Chen et al. [7].
(c) Implementation of bimolecular reversible formal reaction.
Source: Adapted from Qian et al. [16].
In conclusion, from the perspective of theoretical computer science, chemical materials are powerful computing tools. It is capable of performing universal computing, and its programmability can be utilized by designers to create computing systems with desired functions. To fully exploit the computing power of chemical materials, there are researches focusing on the features and organization methods of CRNs and the wet experimental implementation of such systems. More applications of molecular computing are expected in future works.
3.2 Application‐Specific DNA Circuits
In order to take advantage of the merits of DNA computing, researchers do not only use DNA computing to implement Turing machine but also try to employ it for specific applications, especially those involving complex problems. There are two basic questions arising when applying DNA computing for specific applications. One is encoding the real‐world signals to the input variables for CRNs and then decoding them back into real‐world signals after computation (Figure 3.5). The other one is how to design chemical reactions for specific functions.
Figure 3.5 The system performing encoding, computing, and decoding signals