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Engineering high-robustness DNA molecular circuits by utilizing nucleases.
Fu, Shengnan; Li, Na; Li, Junjie; Deng, Yingnan; Xu, Lida; Yu, Changyuan; Su, Xin.
Afiliación
  • Fu S; College of Life Science and Technology, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China. xinsu@mail.buct.edu.cn yucy@mail.buct.edu.cn.
Nanoscale ; 12(13): 6964-6970, 2020 Apr 03.
Article en En | MEDLINE | ID: mdl-32195488
ABSTRACT
Toehold-mediated strand displacement (TMSD) as an important player in DNA nanotechnology has been widely utilized for engineering non-enzymatic molecular circuits. However, these circuits suffer from uncontrollable leakage and unsatisfactory response speed. We utilized site-specific and sequence-independent nucleases to engineer high- robustness DNA molecular circuits. First, we found that the kinetics of the APE1-catalyzed reaction is highly dependent on substrate stability, allowing for the elimination of asymptotic leakage of DNA split circuits. Second, we obtained strict substrate preference of λ exonuclease (λexo) by optimizing the reaction conditions. Robust single-layer and cascade gates with leak resistance were established by using λ exo. Owing to the remarkably fast kinetics of these nucleases, all the circuits yield a high speed of computation. Compared to TMSD-based approaches, nuclease-powered circuits render advanced features such as leakage resistance, hundreds of times higher speed, and simplified structures, representing a class of promising artificial molecule systems.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ADN / Bacteriófago lambda / Computadores Moleculares / Exonucleasas / Proteasas Virales Idioma: En Revista: Nanoscale Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: ADN / Bacteriófago lambda / Computadores Moleculares / Exonucleasas / Proteasas Virales Idioma: En Revista: Nanoscale Año: 2020 Tipo del documento: Article
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