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  • *Movement/drug effects  (1)
  • *Neural Networks (Computer)  (1)
  • *Nucleic Acid Hybridization
  • Nature Publishing Group (NPG)  (2)
  • 1
    Publication Date: 2010-05-14
    Description: Traditional robots rely for their function on computing, to store internal representations of their goals and environment and to coordinate sensing and any actuation of components required in response. Moving robotics to the single-molecule level is possible in principle, but requires facing the limited ability of individual molecules to store complex information and programs. One strategy to overcome this problem is to use systems that can obtain complex behaviour from the interaction of simple robots with their environment. A first step in this direction was the development of DNA walkers, which have developed from being non-autonomous to being capable of directed but brief motion on one-dimensional tracks. Here we demonstrate that previously developed random walkers-so-called molecular spiders that comprise a streptavidin molecule as an inert 'body' and three deoxyribozymes as catalytic 'legs'-show elementary robotic behaviour when interacting with a precisely defined environment. Single-molecule microscopy observations confirm that such walkers achieve directional movement by sensing and modifying tracks of substrate molecules laid out on a two-dimensional DNA origami landscape. When using appropriately designed DNA origami, the molecular spiders autonomously carry out sequences of actions such as 'start', 'follow', 'turn' and 'stop'. We anticipate that this strategy will result in more complex robotic behaviour at the molecular level if additional control mechanisms are incorporated. One example might be interactions between multiple molecular robots leading to collective behaviour; another might be the ability to read and transform secondary cues on the DNA origami landscape as a means of implementing Turing-universal algorithmic behaviour.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907518/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907518/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Lund, Kyle -- Manzo, Anthony J -- Dabby, Nadine -- Michelotti, Nicole -- Johnson-Buck, Alexander -- Nangreave, Jeanette -- Taylor, Steven -- Pei, Renjun -- Stojanovic, Milan N -- Walter, Nils G -- Winfree, Erik -- Yan, Hao -- P41 RR017573/RR/NCRR NIH HHS/ -- P41 RR017573-086704/RR/NCRR NIH HHS/ -- R01 GM062357/GM/NIGMS NIH HHS/ -- R01 GM062357-09/GM/NIGMS NIH HHS/ -- T32 EB005582/EB/NIBIB NIH HHS/ -- T32 EB005582-05/EB/NIBIB NIH HHS/ -- T32 GM008270/GM/NIGMS NIH HHS/ -- T32 GM008270-24/GM/NIGMS NIH HHS/ -- England -- Nature. 2010 May 13;465(7295):206-10. doi: 10.1038/nature09012.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20463735" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Computers, Molecular ; DNA, Catalytic/*metabolism ; DNA, Single-Stranded/chemistry/*metabolism ; Microscopy, Atomic Force ; Microscopy, Fluorescence ; *Movement/drug effects ; Nanotechnology/*methods ; Robotics ; Streptavidin/*chemistry ; Surface Plasmon Resonance ; Time Factors ; Zinc/metabolism/pharmacology
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2011-07-22
    Description: The impressive capabilities of the mammalian brain--ranging from perception, pattern recognition and memory formation to decision making and motor activity control--have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control. Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the 'intelligent' behaviour required for survival. However, the study of how molecules can 'think' has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically, experimental work has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Qian, Lulu -- Winfree, Erik -- Bruck, Jehoshua -- England -- Nature. 2011 Jul 20;475(7356):368-72. doi: 10.1038/nature10262.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Bioengineering, California Institute of Technology, Pasadena, California 91125, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21776082" target="_blank"〉PubMed〈/a〉
    Keywords: Biomimetics ; *Computers, Molecular ; DNA/analysis/*chemistry ; Decision Making ; Memory ; Models, Biological ; Nanotechnology ; *Neural Networks (Computer) ; Neurons ; Synthetic Biology
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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