DNA Computing Boosted by a Cationic Copolymer

Shimada, Noritomo; Saito, Ken; Miyata, Takafumi; Sato, Hiroki; Kobayashi, Satoshi; Maruyama, Atsushi

doi:10.1002/adfm.201707406

Cited by 20 publications

(14 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, circuits immobilized on static scaffolds are sensitive to assembly defects as non- or mis-incorporated reactants will terminate the propagation of the signal along the scaffold. ,, Because the probability of assembly defects increases with the circuit’s complexity, the scalability of immobilized circuits therefore remains challenging. Other efforts to increase the kinetics of DNA strand displacement include the use of RecA as a protein-based catalyst and the use of cationic copolymers, which are postulated to enhance kinetics by stabilizing toehold complex formation. − …”

Section: Introductionmentioning

confidence: 99%

Accelerating DNA-Based Computing on a Supramolecular Polymer

2018

View full text Add to dashboard Cite

Dynamic DNA-based circuits represent versatile systems to perform complex computing operations at the molecular level. However, the majority of DNA circuits relies on freely diffusing reactants, which slows down their rate of operation substantially. Here we introduce the use of DNA-functionalized benzene-1,3,5-tricarboxamide (BTA) supramolecular polymers as dynamic scaffolds to template DNA-based molecular computing. By selectively recruiting DNA circuit components to a supramolecular BTA polymer functionalized with 10-nucleotide handle strands, the kinetics of strand displacement and strand exchange reactions were accelerated 100-fold. In addition, strand exchange reactions were also favored thermodynamically by bivalent interactions between the reaction product and the supramolecular polymer. The noncovalent assembly of the supramolecular polymers enabled straightforward optimization of the polymer composition to best suit various applications. The ability of supramolecular BTA polymers to increase the efficiency of DNA-based computing was demonstrated for three well-known and practically important DNA-computing operations: multi-input AND gates, Catalytic Hairpin Assembly and Hybridization Chain Reactions. This work thus establishes supramolecular BTA polymers as an efficient platform for DNA-based molecular operations, paving the way for the construction of autonomous bionanomolecular systems that confine and combine molecular sensing, computation, and actuation.

show abstract

Section: Introductionmentioning

confidence: 99%

Accelerating DNA-Based Computing on a Supramolecular Polymer

2018

View full text Add to dashboard Cite

show abstract

“…Similarly, to realize the same goal, Maruyama's group showed that a cationic copolymer, poly(llysine)-graft-dextran (PLL-g-Dex), can also elevate the speed of DNA logic operations. [99] This work reduced the operating time from hours-level to minutes-level and also strengthened the nuclease resistance ability of DNA circuits. Although above works evidently improved the computing speed, the used polymers usually need complicated synthesis and purification procedure, this is one problem that needs to be taken seriously in the future.…”

Section: Polymersmentioning

confidence: 92%

Propelling DNA Computing with Materials’ Power: Recent Advancements in Innovative DNA Logic Computing Systems and Smart Bio‐Applications

Fan

Wang

et al. 2020

Advanced Science

View full text Add to dashboard Cite

DNA computing is recognized as one of the most outstanding candidates of next-generation molecular computers that perform Boolean logic using DNAs as basic elements. Benefiting from DNAs' inherent merits of low-cost, easy-synthesis, excellent biocompatibility, and high programmability, DNA computing has evoked substantial interests and gained burgeoning advancements in recent decades, and also exhibited amazing magic in smart bio-applications. In this review, recent achievements of DNA logic computing systems using multifarious materials as building blocks are summarized. Initially, the operating principles and functions of different logic devices (common logic gates, advanced arithmetic and non-arithmetic logic devices, versatile logic library, etc.) are elaborated. Afterward, state-of-the-art DNA computing systems based on diverse "toolbox" materials, including typical functional DNA motifs (aptamer, metal-ion dependent DNAzyme, G-quadruplex, i-motif, triplex, etc.), DNA tool-enzymes, non-DNA biomaterials (natural enzyme, protein, antibody), nanomaterials (AuNPs, magnetic beads, graphene oxide, polydopamine nanoparticles, carbon nanotubes, DNA-templated nanoclusters, upconversion nanoparticles, quantum dots, etc.) or polymers, 2D/3D DNA nanostructures (circular/interlocked DNA, DNA tetrahedron/polyhedron, DNA origami, etc.) are reviewed. The smart bio-applications of DNA computing to the fields of intelligent analysis/diagnosis, cell imaging/therapy, amongst others, are further outlined. More importantly, current "Achilles' heels" and challenges are discussed, and future promising directions of this field are also recommended.

show abstract

“…To realize chemical AI, dependable design methods for recursive DNA circuits must be established, and a variety of new functional molecules must be developed. Cationic copolymers, [ 49 ] which dramatically increase the reaction rate of DNA‐strand displacement, are one such type of functional molecule.…”

Section: Principle Of Learning In Dna Circuitsmentioning

confidence: 99%

Molecular Cybernetics: Challenges toward Cellular Chemical Artificial Intelligence

Murata

Toyota

Nomura

et al. 2022

Adv Funct Materials

View full text Add to dashboard Cite

Research on so-called "chemical artificial intelligence" (CAI) is an emerging field with the aim of constructing information-processing systems with learning capabilities based on chemical methodologies. This can be regarded as an attempt to reconstruct Cybernetics using molecular based systems. Many chemical reaction systems with computational abilities are proposed, but most are fixed functions that deliver molecular output for a given molecular input. On the other hand, chemical AI is a system with learning capability; namely, the output should be variable and gradually change upon repeated molecular inputs. In this paper, a compartmentalization approach for implementing cellular chemical AI using liposomes is discussed. The existing studies in terms of the methods used for assembling systems consisting of many liposomes with different functions, methods for achieving recursiveness and plasticity in chemical reaction systems, and methods for reconfiguring the network topology by liposome deformation are reviewed. Issues that must be addressed in order to realize chemical AI are also identified.

show abstract

DNA Computing Boosted by a Cationic Copolymer

Cited by 20 publications

References 18 publications

Accelerating DNA-Based Computing on a Supramolecular Polymer

Accelerating DNA-Based Computing on a Supramolecular Polymer

Propelling DNA Computing with Materials’ Power: Recent Advancements in Innovative DNA Logic Computing Systems and Smart Bio‐Applications

Molecular Cybernetics: Challenges toward Cellular Chemical Artificial Intelligence

Contact Info

Product

Resources

About