Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 128-130___________________________________________________________________________________________________________

Toward Artificial Intelligence by using DNA molecules
Yasuhiro Suzuki

Graduate School of Informatics, Nagoya University, Furocho
Chikusa, Nagoya city 464-0814, Japan
Rie Taniguchi

Graduate School of Informatics, Nagoya University, Furocho
Chikusa, Nagoya city 464-0814, Japan
E-mail: ysuzuki@nagoya-u.jp
http://ysuzuki.info

Abstract
Molecule Robotics have been realized by using bio molecules such as DNA, proteins, for example in Molecular
Robotics Research Project [2012-17, JSPS]; bio molecules, such as DNA or proteins are highly structured and they
already have a kind of “intelligence” and adapt to environment change. Hence, we have tried to extract their“ability” and induce Intelligence artificially. We have used well-known DNA reactions, Seesaw gate reaction andwe found that DNA molecule can sense concentration of single strand input sequence or quasi-input (including
mismatched base pairs and point mutations in the sequence) and chooses higher concentration one; this resultshows DNA molecule (short DNA sequence) can adapt to its environment.
Keywords: DNA computing, Molecular Robotics, Strand Displacement Reactions

from motor proteins to the membrane and the shape ofthe body changes. Gears of the clutch are changed by asignal molecule composed of sequence-designed DNA.

1. Introduction
Adelman solved Hamilton Path Problem by using acomputer, which was synthesized by DNA molecules.
His research opens up novel era of molecular computing.
DNA computing has evolved as a method of Bonino
technology and realized a molecular robot.
For example, S. Nomura’s team has chemically
implemented a molecular robot [1]. This robot iscomposed of bio molecules, which are composed of abody, an actuator, and an actuator-controlling device(clutch); whose body is composed of a lipid bilayer, theactuator consists of proteins including kinesin, andmicrotubules and the clutch made of designed DNA
molecules. This clutch transmits the generated force

2. Molecular Artificial Intelligence
Artificial Intelligence, AI has developed on electricaldevice, where all information is coded as electricalsignals. On the other hand, in a molecular robot all
information is coded as chemicals such as DNA orproteins. Hence, if we can realize Artificial Intelligenceby using chemicals, we will be able to give intelligenceto the molecular robots.

Copyright © 2018, the Authors. Published by Atlantis Press.
This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 128-130___________________________________________________________________________________________________________

2.1. Abstract Chemical Reactions by DNA

double strand DNA through random-walk like; thecomplementary single-stranded domains are called astoeholds. In this reaction, at least one single stranded
nucleic acid is released and this released strand canevoke downstream reactions. Since branch migration
does not change the free energy during the reaction of
exchanging strand pairs, it can be described by arandom walk process with equal transitions probabilities
of displacement in both directions at each position of
the branch point [5].

Several logical gates have been realized by using DNA[4]. Various simulations of Abstract ChemicalReactions, ACR based on Chemical kinetic have been
made by using the DNA logical gates [3]. For example,
Fujii et. al. [5] chemically implemented the LotokaVorterra, LV model and showed that their reaction canrealize the same behavior to analytic solution of LV
model by differential equations.
Quian et.al., have proposed collection of DNA
reactions as a “toolbox” to implement ACR by using
DNA; they showed that an Artificial Neural Network
can be implemented by using the toolbox [3].
3. Intelligence of Molecular Robot
Philosopher, prof. Kazuhisa Todayama has argued apossible development of philosophy as Concept
Engineering. Concept engineering provides novel
concept based on thinkers’ assets. For example, in thecase when we have to face difficult problems such as
creating a regulation for robots in order to ready for acase when a fully autonomous intelligent robot kills ahuman. In such a case, philosophers can provide wide
varieties of concepts from different aspects and they cansupport to create a novel concept through collaboratingwith specialists and citizens. Todayama points out that
Human right is a legacy of concept engineering, which
has been invented by philosophers based on the asset ofphilosophy [2,3].
3.1. How to create intelligence in molecular robots

Fig.1. Strand displacement reaction; In this example, the shortstrand, which is denoted as an arrow binds to the toehold
domains, through branch migration process across region 2,
the strand is displaced and freed from the complex.

Todayama proposed how to create intelligence in amolecular robot from concept engineering view point; if
we let the molecular robot free as possible as we canand if the robot can have own purpose, intelligence will
be emerged, where any purpose is granted and no matter
how it is simple or not, it is important to have its own
purpose. In order to create molecular AI, we give apurpose to a robot, which is maintaining its self.
4.

In order to implement molecular AI, we modified theSeesaw gate reaction [4]; since this reaction is selfmaintaining reaction, we can give the reactions a
purpose as self-maintaining. These reactions arecomposed of basically two strand displacement
reactions; input + gate:fuel ↔ gate:input + fuel (1) andgate:output + input ↔ gate:input + output (2); in orderto confirm the reactions circulate, we used the following
reaction;

Methods

Chemical reactions in the toolbox are mainly
modification of the toehold strand displacement reactionof DNA. Strand displacement reaction is initiated fromcomplementary single-stranded domains and branchmigration process exchanges a single strand DNA with129

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 2 (September 2018) 128-130___________________________________________________________________________________________________________

fuel + gate(Quencher):output input(Fluorescence) ↔
gate(Quencher):input(Fluorescence) + output +gate(Quencher):fuel (3).

Fig. 2. Seesaw gate reaction [4]: (a) Abstract gate diagram.
Red numbers indicate initial concentrations. (b) The DNA gate
motif and reaction mechanism. S1, S2, S3 and S4 are therecognition domains; T is the toehold domain; T0 is theWatson–Crick complement of T, etc. Arrowheads mark the 30
ends of strands. Signal strands are named by their domains
from 30 to 50, All reactions are reversible and unbiased; solidlines indicate the dominant flows for the initial concentrations
shown in (a), while the reverse reactions are dotted. (c)5.

Fig. 3. Time series of concentration of Input sequences
obtained by the real time PCR: (Upper) No input sequence,(Lower) Input sequences without toehold, the concentration ofinput sequences decreased through binding to gate:output
sequences. CY3 and ROX are fluorescent dyes to label DNAsequences.

Acknowledgement

ResultProf. Ken Komiya (Tokyo Institute of Tech.) gives
insightful comments and suggestions. This research wassupported by KAKENHI Grant No. 24104003 (JSPS)
and 16H03093 (MEXT).
References

From biochemical experiments, we observed that when
we added non-mutated input and mutated input, thesystem selected higher concentration one (Fig.3). And
we also confirmed the behaviors in the time series of theconcentration of normal input and mutated input
sequences showed oscillations (Fig.3). And when theconcentration decreased, the concentration of another
input increased, hence we conjecture that the systemselects higher concentration one because the selected
input sequences were switched among non-mutated andmutated input sequences. These results illustrate that thesystem made of DNA reaction networks is able to selectinput sequences in higher concentration so it will beable to adapt to the environmental change. Therefore,
from biological and philosophical points of views, thissystem realizes molecular Artificial Intelligence (Fig.3).

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