Homogeneous assays based on deoxyribozyme catalysis

Stojanović, Milan N.; Prada, Paloma de; Landry, Donald W.

doi:10.1093/nar/28.15.2915

Cited by 47 publications

(26 citation statements)

References 18 publications

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“…RNA-cleaving deoxyribozymes can be used directly as oligonucleotide sensors via a catalytic molecular beacon design [136] or via an approach involving a binary deoxyribozyme, in which the oligonucleotide target is the platform for assembling the functional DNA enzyme from two fragments [137]. An RNA-cleaving deoxyribozyme has also been used to detect streptavidin upon its binding to biotin covalently attached to the DNA near the active site, thereby inhibiting catalysis [138]. A general conclusion is that deoxyribozymes are well-behaved components of molecular-scale sensors, for which ingenuity and necessity appear to be the limiting design factors.…”

Section: Regulated Rna-cleaving Deoxyribozymes As Sensorsmentioning

confidence: 99%

Deoxyribozymes: useful DNA catalysts in vitro and in vivo

Baum

Silverman

2008

Cell. Mol. Life Sci.

165

129

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Deoxyribozymes (DNA enzymes; DNAzymes) are catalytic DNA sequences. Using the technique of in vitro selection, individual deoxyribozymes have been identified that catalyze RNA cleavage, RNA ligation, and a growing range of other chemical reactions. DNA enzymes have been used in vitro for applications such as biochemical RNA manipulation and analytical assays for metal ions, small organic compounds, oligonucleotides, and proteins. Deoxyribozymes have also been utilized as in vivo therapeutic agents to destroy specific mRNA targets. Although many conceptual and practical challenges remain to be addressed, deoxyribozymes have substantial promise to contribute meaningfully for applications both in vitro and in vivo.

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Section: Regulated Rna-cleaving Deoxyribozymes As Sensorsmentioning

confidence: 99%

Deoxyribozymes: useful DNA catalysts in vitro and in vivo

Baum

Silverman

2008

Cell. Mol. Life Sci.

165

129

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“…Hybridization with a complementary DNA strand releases the inhibitor from the active site and switches on protease activity (Saghatelian et al, 2003). Deoxyribozymes and ribozymes (nucleic acids that behave as enzymes) with nuclease activity have been used to construct catalytic molecular beacons (Stojanovic et al, 2001) or sensors for non-nucleic acid compounds (Ferguson et al, 2004;Frauendorf and Jaschke, 2001;Stojanovic et al, 2000). The sensitivity of catalytic sensors depends on the difference in catalytic activity between the free and effector-bound enzymes.…”

Section: Catalytic Amplification Of the Signalmentioning

confidence: 99%

Fluorescence sensing of intermolecular interactions and development of direct molecular biosensors

2006

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Molecular biosensors are devices of molecular size that are designed for sensing different analytes on the basis of biospecific recognition. They should provide two coupled functions - the recognition (specific binding) of the target and the transduction of information about the recognition event into a measurable signal. The present review highlights the achievements and prospects in design and operation of molecular biosensors for which the transduction mechanism is based on fluorescence. We focus on the general strategy of fluorescent molecular sensing, construction of sensor elements, based on natural and designed biopolymers (proteins and nucleic acids). Particular attention is given to the coupling of sensing elements with fluorescent reporter dyes and to the methods for producing efficient fluorescence responses.

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“…Their reactions and rates provide a universal description that all chemists understand and consequently can translate to the implementation substrate of their choice, such as DNA hybridization [140,166], or deoxyribozymes [95,143,145].…”

Section: Basic Speciesmentioning

confidence: 99%

Novel Methods for Learning and Adaptation in Chemical Reaction Networks

Banda¹

2000

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State-of-the-art biochemical systems for medical applications and chemical computing are application-specific and cannot be re-programmed or trained once fabricated. The implementation of adaptive biochemical systems that would offer flexibility through programmability and autonomous adaptation faces major challenges because of the large number of required chemical species as well as the timing-sensitive feedback loops required for learning. Currently, biochemistry lacks a systems vision on how the userlevel programming interface and abstraction with a subsequent translation to chemistry should look like. By developing adaptation in chemistry, we could replace multiple hardwired systems with a single programmable template that can be (re)trained to match a desired input-output profile benefiting smart drug delivery, pattern recognition, and chemical computing.I aimed to address these challenges by proposing several approaches to learning and adaptation in Chemical Reaction Networks (CRNs), a type of simulated chemistry, where species are unstructured, i.e., they are identified by symbols rather than molecular structure, and their dynamics or concentration evolution are driven by reactions and reaction rates that follow mass-action and Michaelis-Menten kinetics.Several CRN and experimental DNA-based models of neural networks exist. However, these models successfully implement only the forward-pass, i.e., the input-weight integration part of a perceptron model. Learning is delegated to a non-chemical system that i computes the weights before converting them to molecular concentrations. Autonomous learning, i.e., learning implemented fully inside chemistry has been absent from both theoretical and experimental research.The research in this thesis offers the first constructive evidence that learning in CRNs is, in fact, possible. I have introduced the original concept of a chemical binary perceptron that can learn all 14 linearly-separable logic functions and is robust to the perturbation of rate constants. That shows learning is universal and substrate-free. To simplify the model I later proposed and applied the "asymmetric" chemical arithmetic providing a compact solution for representing negative numbers in chemistry.To tackle more difficult tasks and to serve more complicated biochemical applications, I introduced several key modular building blocks, each addressing certain aspects of chemical information processing and learning. These parts organically combined into gradually more complex systems. First, instead of simple static Boolean functions, I tackled analog time-series learning and signal processing by modeling an analog chemical perceptron. To store past input concentrations as a sliding window I implemented a chemical delay line, which feeds the values to the underlying chemical perceptron. That allows the system to learn, e.g., the linear moving-average and to some degree predict a highly nonlinear NARMA benchmark series.Another important contribution to the area of chemical learning, which I ...

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Homogeneous assays based on deoxyribozyme catalysis

Cited by 47 publications

References 18 publications

Deoxyribozymes: useful DNA catalysts in vitro and in vivo

Deoxyribozymes: useful DNA catalysts in vitro and in vivo

Fluorescence sensing of intermolecular interactions and development of direct molecular biosensors

Novel Methods for Learning and Adaptation in Chemical Reaction Networks

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