Details

Enzyme-Based Computing Systems


Enzyme-Based Computing Systems


1. Aufl.

von: Evgeny Katz

142,99 €

Verlag: Wiley-VCH
Format: EPUB
Veröffentl.: 10.06.2019
ISBN/EAN: 9783527819980
Sprache: englisch
Anzahl Seiten: 424

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

This systematic and comprehensive overview of enzyme-based biocomputing is an excellent resource for scientists and engineers working on the design, study and applications of enzyme-logic systems.
<p>Preface xv</p> <p>Acknowledgment xvii</p> <p>List of Abbreviations xxiii</p> <p><b>1 Introduction </b><b>1</b></p> <p>1.1 Motivation and Applications 1</p> <p>1.2 Enzyme-Based Logic Gates and Short Logic Circuits 3</p> <p>References 5</p> <p><b>2 Boolean Logic Gates Realized with Enzyme-Catalyzed Reactions: Unusual Look at Usual Chemical Reactions </b><b>9</b></p> <p>2.1 General Introduction and Definitions 9</p> <p>2.2 Fundamental Boolean Logic Operations Mimicked with Enzyme-Catalyzed Reactions 11</p> <p>2.2.1 Identity (YES) Gate 11</p> <p>2.2.2 Inverted Identity (NOT) Gate 12</p> <p>2.2.3 OR Gate 13</p> <p>2.2.4 NOR Gate 15</p> <p>2.2.5 XOR Gate 15</p> <p>2.2.6 NXOR Gate 18</p> <p>2.2.7 AND Gate 20</p> <p>2.2.8 NAND Gate 21</p> <p>2.2.9 INHIB Gate 22</p> <p>2.2.10 Summary on the Basic Boolean Gates Realized with Enzyme Systems 23</p> <p>2.3 Modular Design of NOR and NAND Logic Gates 24</p> <p>2.4 Majority and Minority Logic Gates 28</p> <p>2.5 Reconfigurable Logic Gates 34</p> <p>2.5.1 3-Input Logic Gates Switchable Between AND–OR Logic Functions Operating in a Solution 34</p> <p>2.5.2 Enzyme-Based Logic Gates Switchable Between OR, NXOR, and NAND Boolean Operations Realized in a Flow System 35</p> <p>2.6 Conclusions and Perspectives 40</p> <p>References 41</p> <p><b>3 Optimization of Enzyme-Based Logic Gates for Reducing Noise in the Signal Transduction Process </b><b>47</b></p> <p>3.1 Introduction 47</p> <p>3.2 Signal Transduction Function in the Enzyme-Based Logic Systems: Filters Producing Sigmoid Response Functions 48</p> <p>3.2.1 Identity (YES) Logic Gate Optimization 50</p> <p>3.2.2 AND Logic Gate Optimization 52</p> <p>3.2.3 OR Logic Gate Optimization 55</p> <p>3.2.4 XOR Logic Gate Optimization 56</p> <p>3.3 Summary 59</p> <p>References 59</p> <p><b>4 Enzyme-Based Short Logic Networks Composed of Concatenated Logic Gates </b><b>63</b></p> <p>4.1 Introduction: Problems in Assembling of Multistep Logic Networks 63</p> <p>4.2 Logic Network Composed of Concatenated Gates: An Example System 64</p> <p>4.3 Logic Networks with Suppressed Noise in the Presence of Filter Systems 66</p> <p>4.4 Logic Circuits Activated with Biomolecular Signals and Magnetic Field Applied 68</p> <p>4.4.1 Biocatalytic Reactions Proceeding with Bulk Diffusion of Intermediate Substrates/Products and with Their Channeling 68</p> <p>4.4.2 Magneto-Controlled Biocatalytic Cascade Switchable Between Substrate Diffusion and Substrate Channeling Modes of Operation 69</p> <p>4.4.3 Logic Signal Processing with the Switchable Biocatalytic System 72</p> <p>4.5 The Summary: Step Forward from Single Logic Gates to Complex Logic Circuits 74</p> <p>References 75</p> <p><b>5 Sophisticated Reversible Logic Systems </b><b>79</b></p> <p>5.1 Introduction 79</p> <p>5.1.1 Reversible Logic Gates and Their Features 79</p> <p>5.1.2 Logic Reversibility vs. Physical Reversibility 80</p> <p>5.1.3 Integration of Reversible Logic Gates into Biomolecular Computing Systems 81</p> <p>5.1.4 Spatial Separation of Enzyme Logic Operation: The Use of Flow Devices 81</p> <p>5.2 Feynman Gate: Controlled NOT (CNOT) Gate 82</p> <p>5.3 Double Feynman Gate (DFG) Operation 86</p> <p>5.4 Toffoli Gate Operation 90</p> <p>5.5 Peres Gate Operation 94</p> <p>5.6 Gates Redirecting Output Signals 99</p> <p>5.6.1 Controlled-Switch Gate 99</p> <p>5.6.2 Fredkin (Controlled-Swap) Gate 102</p> <p>5.7 Advantages and Disadvantages of the Developed Approach 107</p> <p>5.7.1 Advantages 107</p> <p>5.7.2 Disadvantages 108</p> <p>5.8 Conclusions and Perspectives 109</p> <p>References 109</p> <p><b>6 Transduction of Signals Generated by Enzyme Logic Gates </b><b>113</b></p> <p>6.1 Optical Analysis of Output Signals Generated by Enzyme-Based Logic Systems 113</p> <p>6.1.1 Optical Absorbance Measurements for Transduction of Output Signals Produced by Enzyme-Based Logic Gates 114</p> <p>6.1.2 Bioluminescence Measurements for Transduction of Output Signals Produced by Enzyme-Based Logic Gates 120</p> <p>6.1.3 Surface Plasmon Resonance (SPR) Measurements for Transduction of Output Signals Produced by Enzyme-Based Logic Gates 121</p> <p>6.2 Electrochemical Analysis of Output Signals Generated by Enzyme-Based Logic Systems 122</p> <p>6.2.1 Chronoamperometric Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 123</p> <p>6.2.2 Potentiometric Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 124</p> <p>6.2.3 pH Measurements as a Tool for Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 126</p> <p>6.2.4 Indirect Electrochemical Analysis of Output Signals Generated by Enzyme-Based Logic Systems Using Electrodes Functionalized with pH-Switchable Polymers 127</p> <p>6.2.5 ConductivityMeasurements as a Tool for Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 130</p> <p>6.2.6 Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems Using Semiconductor Devices 132</p> <p>6.3 Macro/Micro/Nano-mechanical Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 134</p> <p>6.3.1 Mechanical Bending of a Cantilever Used for Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 135</p> <p>6.3.2 Quartz Crystal Microbalance (QCM) Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 137</p> <p>6.3.3 Atomic Force Microscopy (AFM) Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 138</p> <p>6.4 Conclusions and Perspectives 142</p> <p>References 143</p> <p><b>7 Circuit Elements Based on Enzyme Systems </b><b>151</b></p> <p>7.1 Enzyme-Based Multiplexer and Demultiplexer 151</p> <p>7.1.1 General Definition of the Multiplexer and Demultiplexer Functions 151</p> <p>7.1.2 2-to-1 DigitalMultiplexer Based on the Enzyme-Catalyzed Reactions 153</p> <p>7.1.3 1-to-2 Digital Demultiplexer Based on the Enzyme-Catalyzed Reactions 155</p> <p>7.1.4 1-to-2 Digital Demultiplexer Interfaced with an Electrochemical Actuator 158</p> <p>7.2 Biomolecular Signal Amplifier Based on Enzyme-Catalyzed Reactions 164</p> <p>7.3 Biomolecular Signal Converter Based on Enzyme-Catalyzed Reactions 166</p> <p>7.4 Utilization of a Fluidic Infrastructure for the Realization of Enzyme-Based Boolean Logic Circuits 167</p> <p>7.5 Other Circuit Elements Required for the Networking of Enzyme Logic Systems and General Conclusions 169</p> <p>References 170</p> <p><b>8 Enzyme-Based Memory Systems </b><b>175</b></p> <p>8.1 Introduction 175</p> <p>8.2 Enzyme-Based Flip-Flop Memory Elements 175</p> <p>8.2.1 Set/Reset (SR) Flip-Flop Memory Based on Enzyme-Catalyzed Reactions 176</p> <p>8.2.2 Delay (D) Flip-Flop Memory Based on Enzyme-Catalyzed Reactions 182</p> <p>8.2.3 Toggle (T) Flip-Flop Memory Based on Enzyme-Catalyzed Reactions 185</p> <p>8.2.4 Enzyme-Based Flip-Flop Memory Systems: Conclusions and Perspectives 186</p> <p>8.3 Memristor Based on Enzyme Biocatalytic Reactions 188</p> <p>8.3.1 Memristors: From Semiconductor Devices to Soft Matter and Biomolecular Materials 188</p> <p>8.3.2 The Memristor Device Based on a Biofuel Cell 189</p> <p>8.3.3 The Memristor Device Controlled by Logically Processed Biomolecular Signals 196</p> <p>8.3.4 Enzyme-Based Memristors: Conclusions and Perspectives 198</p> <p>8.4 Enzyme-Based Associative Memory Systems 198</p> <p>8.4.1 Associative Memory: Biological Origin and Function 199</p> <p>8.4.2 Realization of the Associative Memory with a Multienzyme Biocatalytic Cascade 201</p> <p>8.4.3 Enzyme-Based Associative Memory: Challenges and Perspectives 203</p> <p>8.5 Enzyme-Based Memory Systems: Challenges, Perspectives, and Limitations 204</p> <p>References 206</p> <p><b>9 Arithmetic Functions Realized with Enzyme-Catalyzed Reactions </b><b>211</b></p> <p>9.1 Molecular and Biomolecular Arithmetic Systems: Introduction and Motivation 211</p> <p>9.2 Half-Adder 212</p> <p>9.3 Half-Subtractor 216</p> <p>9.4 Conclusions and Perspectives 219</p> <p>References 219</p> <p><b>10 Information Security Applications Based on Enzyme Logic Systems </b><b>223</b></p> <p>10.1 Keypad Lock Devices as Examples of Electronic Information Security Systems 223</p> <p>10.2 Keypad Lock Systems Based on Biocatalytic Cascades 224</p> <p>10.3 Other Biomolecular Information Security Systems 229</p> <p>10.3.1 Steganography and EncryptionMethods Based on Bioaffinity Complex Formation Followed by a Biocatalytic Reaction 229</p> <p>10.3.2 Barcodes Produced by Bioelectrocatalytic Reactions 231</p> <p>10.4 Summary 233</p> <p>References 233</p> <p><b>11 Enzyme Logic Digital Biosensors for Biomedical, Forensic, and Security Applications </b><b>235</b></p> <p>11.1 Introduction: Short Overview 235</p> <p>11.2 From Traditional Analog Biosensors to Novel Binary Biosensors Based on the Biocomputing Concept 235</p> <p>11.3 How Binary Operating Biosensors Can Benefit Biomedical Analysis: Requirements, Challenges, and First Applications 238</p> <p>11.4 Binary (YES/NO) Analysis of Liver Injury Biomarkers: From Test Tube Probes to Animal Research 240</p> <p>11.5 Further Examples of Injury Biomarker Analysis Using AND/NAND Logic Gates 245</p> <p>11.5.1 Soft Tissue Injury (STI) Logic Analysis 246</p> <p>11.5.2 Traumatic Brain Injury (TBI) Logic Analysis 247</p> <p>11.5.3 Abdominal Trauma (ABT) Logic Analysis 250</p> <p>11.5.4 Hemorrhagic Shock (HS) Logic Analysis 251</p> <p>11.5.5 Oxidative Stress (OS) Logic Analysis 254</p> <p>11.5.6 Radiation Injury (RI) Logic Analysis 258</p> <p>11.6 Multienzyme Logic Network Architectures for Assessing Injuries: Aiming at the Increased Complexity of the Biocomputing–Bioanalytic Systems 261</p> <p>11.6.1 The System Structure Based on the Complex Biocatalytic Cascade 261</p> <p>11.6.2 STI Operation Mode of the Logic Network 264</p> <p>11.6.3 TBI Operation Mode of the Logic Network 265</p> <p>11.6.4 Switching Between the STI and TBI Modes and General Comments on the System 267</p> <p>11.7 New Approach in Forensic Analysis: Biomolecular Computing-Based Analysis of Forensic Biomarkers 268</p> <p>11.8 Logic Analysis of Security Threats (Explosives and Nerve Agents) Based on Biocatalytic Cascades 270</p> <p>11.9 Integration of Biocatalytic Cascades with Microelectronics and Wearable Sensors 272</p> <p>11.10 Conclusions and Perspectives 276</p> <p>References 276</p> <p><b>12 Release of Molecular Species Stimulated by Logically Processed Biomolecule Signals </b><b>283</b></p> <p>12.1 Motivation and Experimental Background 283</p> <p>12.2 Fe<sup>3+</sup>-Cross-Linked Alginate Hydrogel is a Good Example of Matrix for Signal-Stimulated Release 284</p> <p>12.3 DNA Release as an Example of Signal-Stimulated Biomolecule Release 287</p> <p>12.4 Bioelectrochemical Systems with Sensing and Releasing Electrodes 287</p> <p>12.4.1 Sensing Electrodes Activated with Single Input Identity Gate 288</p> <p>12.4.2 Sensing Electrodes Activated with Multi-input Logic Networks 288</p> <p>12.4.3 Releasing Electrodes: Various Released Species for Different Applications 291</p> <p>12.5 Fe<sup>3+</sup>-Cross-Linked Alginate Hydrogel Decomposition and Entrapped Molecule Release Triggered by Enzymatically Produced H<sub>2</sub>O<sub>2 </sub>294</p> <p>12.5.1 DNA Release from Fe<sup>3+</sup>-Cross-Linked Alginate Hydrogel Stimulated by Signals Processed through OR, AND, and INHIB Logic Gates 294</p> <p>12.5.2 DNA Release from Fe<sup>3+</sup>-Cross-Linked Alginate Hydrogel Stimulated by Signals Processed Through Multi-gate Network Composed of Concatenated AND Gates 304</p> <p>12.6 Conclusions and Perspectives 307</p> <p>References 307</p> <p><b>13 Biofuel Cells Controlled by Biocomputing Systems </b><b>313</b></p> <p>13.1 Introduction: Biofuel Cells,Their Applications, and Motivation for Designing Adaptive, Signal-Controlled Devices 313</p> <p>13.2 Biofuel Cells Controlled by Logically Processed Biochemical Signals 315</p> <p>13.3 Biofuel Cells Controlled by Biomolecular Keypad Lock Systems 326</p> <p>13.4 Conclusions and Perspectives 328</p> <p>References 330</p> <p><b>14 Bioelectronic Interface Between Enzyme-Based and DNA-Based Computing Systems </b><b>335</b></p> <p>14.1 Introduction: Interfacing Enzyme-Based and DNA-Based Computing Systems Is a Challenging Goal 335</p> <p>14.2 Bioelectronic Interface Transducing Logically Processed Signals from an Enzymatic System to a DNA System 336</p> <p>14.3 The Bioelectronic Interface Connecting Enzyme-Based Reversible Logic Gates and DNA-Based Reversible Logic Gates: Realization in a Flow Device 344</p> <p>14.3.1 Enzyme-Based Fredkin Gate Processing Biomolecular Signals Prior to the Bioelectronic Interface 345</p> <p>14.3.2 Reversible DNA-Based Feynman Gate Activated by Signals Produced by the Enzyme-Based Fredkin Gate 348</p> <p>14.4 Conclusions and Perspectives 351</p> <p>References 352</p> <p><b>15 What Is Next? Mimicking Natural Biological Information Processes </b><b>357</b></p> <p>15.1 Motivation and Goals 357</p> <p>15.2 Example and Discussion of Feed Forward Loops 358</p> <p>15.3 Enzymatic Feed-Forward Loops 360</p> <p>15.4 Process Design and Kinetic Modeling 364</p> <p>15.5 Simpler Biocatalytic Systems<b>: </b>Not a Feed-Forward Loop Yet 366</p> <p>15.6 Conclusion 367</p> <p>References 368</p> <p><b>16 Conclusions and Perspectives: Where Are We Going? </b><b>371</b></p> <p>16.1 Conclusions 371</p> <p>16.2 Perspectives 373</p> <p>16.2.1 Information Processing Through Complex Biological Pathways in Cells 374</p> <p>16.2.2 Signal-Controlled Bioelectronic Devices and Signal-Triggered Molecular Release 375</p> <p>16.2.3 Allosteric and Hybrid Enzymes 375</p> <p>16.2.4 Enzyme System Controlled by Various Chemical and Physical Signals 377</p> <p>16.2.5 Molecular and Nanomachines for Self-Propulsion and Logic Operation 378</p> <p>16.3 Final Comments 379</p> <p>References 380</p> <p>Index 383 </p>
Evgeny Katz received his Ph.D. in Chemistry from Frumkin Institute of Electrochemistry (Moscow), Russian Academy of Sciences, in 1983. He was a senior researcher in the Institute of Photosynthesis (Pushchino), Russian Academy of Sciences, in 1983-1991. In 1992-1993 he performed research at München Technische Universität (Germany) as a Humboldt fellow. Later, in 1993-2006, Dr. Katz was a Research Associate Professor at the Hebrew University of Jerusalem. Since 2006 he is Milton Kerker Chaired Professor at the Department of Chemistry and Biomolecular Science, Clarkson University, NY (USA). His scientific interests are in the broad areas of bioelectronics, biosensors, biofuel cells, biomolecular information processing and recently in forensic science.

Diese Produkte könnten Sie auch interessieren:

Terpene
Terpene
von: Eberhard Breitmaier
PDF ebook
40,99 €
Reaktionen der organischen Chemie
Reaktionen der organischen Chemie
von: Helmut Krauch, Werner Kunz
PDF ebook
124,99 €
Sieben Moleküle
Sieben Moleküle
von: Jürgen-Hinrich Fuhrhop, Tianyu Wang
PDF ebook
25,99 €