Enzyme-based Computing Systems
, by Katz, Evgeny
- ISBN: 9783527345700 | 3527345701
- Cover: Hardcover
- Copyright: 10/7/2019
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.
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.
Preface xv
Acknowledgment xvii
List of Abbreviations xxiii
1 Introduction 1
1.1 Motivation and Applications 1
1.2 Enzyme-Based Logic Gates and Short Logic Circuits 3
References 5
2 Boolean Logic Gates Realized with Enzyme-Catalyzed Reactions: Unusual Look at Usual Chemical Reactions 9
2.1 General Introduction and Definitions 9
2.2 Fundamental Boolean Logic Operations Mimicked with Enzyme-Catalyzed Reactions 11
2.2.1 Identity (YES) Gate 11
2.2.2 Inverted Identity (NOT) Gate 12
2.2.3 OR Gate 13
2.2.4 NOR Gate 15
2.2.5 XOR Gate 15
2.2.6 NXOR Gate 18
2.2.7 AND Gate 20
2.2.8 NAND Gate 21
2.2.9 INHIB Gate 22
2.2.10 Summary on the Basic Boolean Gates Realized with Enzyme Systems 23
2.3 Modular Design of NOR and NAND Logic Gates 24
2.4 Majority and Minority Logic Gates 28
2.5 Reconfigurable Logic Gates 34
2.5.1 3-Input Logic Gates Switchable Between AND–OR Logic Functions Operating in a Solution 34
2.5.2 Enzyme-Based Logic Gates Switchable Between OR, NXOR, and NAND Boolean Operations Realized in a Flow System 35
2.6 Conclusions and Perspectives 40
References 41
3 Optimization of Enzyme-Based Logic Gates for Reducing Noise in the Signal Transduction Process 47
3.1 Introduction 47
3.2 Signal Transduction Function in the Enzyme-Based Logic Systems: Filters Producing Sigmoid Response Functions 48
3.2.1 Identity (YES) Logic Gate Optimization 50
3.2.2 AND Logic Gate Optimization 52
3.2.3 OR Logic Gate Optimization 55
3.2.4 XOR Logic Gate Optimization 56
3.3 Summary 59
References 59
4 Enzyme-Based Short Logic Networks Composed of Concatenated Logic Gates 63
4.1 Introduction: Problems in Assembling of Multistep Logic Networks 63
4.2 Logic Network Composed of Concatenated Gates: An Example System 64
4.3 Logic Networks with Suppressed Noise in the Presence of Filter Systems 66
4.4 Logic Circuits Activated with Biomolecular Signals and Magnetic Field Applied 68
4.4.1 Biocatalytic Reactions Proceeding with Bulk Diffusion of Intermediate Substrates/Products and with Their Channeling 68
4.4.2 Magneto-Controlled Biocatalytic Cascade Switchable Between Substrate Diffusion and Substrate Channeling Modes of Operation 69
4.4.3 Logic Signal Processing with the Switchable Biocatalytic System 72
4.5 The Summary: Step Forward from Single Logic Gates to Complex Logic Circuits 74
References 75
5 Sophisticated Reversible Logic Systems 79
5.1 Introduction 79
5.1.1 Reversible Logic Gates and Their Features 79
5.1.2 Logic Reversibility vs. Physical Reversibility 80
5.1.3 Integration of Reversible Logic Gates into Biomolecular Computing Systems 81
5.1.4 Spatial Separation of Enzyme Logic Operation: The Use of Flow Devices 81
5.2 Feynman Gate: Controlled NOT (CNOT) Gate 82
5.3 Double Feynman Gate (DFG) Operation 86
5.4 Toffoli Gate Operation 90
5.5 Peres Gate Operation 94
5.6 Gates Redirecting Output Signals 99
5.6.1 Controlled-Switch Gate 99
5.6.2 Fredkin (Controlled-Swap) Gate 102
5.7 Advantages and Disadvantages of the Developed Approach 107
5.7.1 Advantages 107
5.7.2 Disadvantages 108
5.8 Conclusions and Perspectives 109
References 109
6 Transduction of Signals Generated by Enzyme Logic Gates 113
6.1 Optical Analysis of Output Signals Generated by Enzyme-Based Logic Systems 113
6.1.1 Optical Absorbance Measurements for Transduction of Output Signals Produced by Enzyme-Based Logic Gates 114
6.1.2 Bioluminescence Measurements for Transduction of Output Signals Produced by Enzyme-Based Logic Gates 120
6.1.3 Surface Plasmon Resonance (SPR) Measurements for Transduction of Output Signals Produced by Enzyme-Based Logic Gates 121
6.2 Electrochemical Analysis of Output Signals Generated by Enzyme-Based Logic Systems 122
6.2.1 Chronoamperometric Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 123
6.2.2 Potentiometric Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 124
6.2.3 pH Measurements as a Tool for Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 126
6.2.4 Indirect Electrochemical Analysis of Output Signals Generated by Enzyme-Based Logic Systems Using Electrodes Functionalized with pH-Switchable Polymers 127
6.2.5 ConductivityMeasurements as a Tool for Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 130
6.2.6 Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems Using Semiconductor Devices 132
6.3 Macro/Micro/Nano-mechanical Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 134
6.3.1 Mechanical Bending of a Cantilever Used for Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 135
6.3.2 Quartz Crystal Microbalance (QCM) Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 137
6.3.3 Atomic Force Microscopy (AFM) Transduction of Chemical Output Signals Produced by Enzyme-Based Logic Systems 138
6.4 Conclusions and Perspectives 142
References 143
7 Circuit Elements Based on Enzyme Systems 151
7.1 Enzyme-Based Multiplexer and Demultiplexer 151
7.1.1 General Definition of the Multiplexer and Demultiplexer Functions 151
7.1.2 2-to-1 DigitalMultiplexer Based on the Enzyme-Catalyzed Reactions 153
7.1.3 1-to-2 Digital Demultiplexer Based on the Enzyme-Catalyzed Reactions 155
7.1.4 1-to-2 Digital Demultiplexer Interfaced with an Electrochemical Actuator 158
7.2 Biomolecular Signal Amplifier Based on Enzyme-Catalyzed Reactions 164
7.3 Biomolecular Signal Converter Based on Enzyme-Catalyzed Reactions 166
7.4 Utilization of a Fluidic Infrastructure for the Realization of Enzyme-Based Boolean Logic Circuits 167
7.5 Other Circuit Elements Required for the Networking of Enzyme Logic Systems and General Conclusions 169
References 170
8 Enzyme-Based Memory Systems 175
8.1 Introduction 175
8.2 Enzyme-Based Flip-Flop Memory Elements 175
8.2.1 Set/Reset (SR) Flip-Flop Memory Based on Enzyme-Catalyzed Reactions 176
8.2.2 Delay (D) Flip-Flop Memory Based on Enzyme-Catalyzed Reactions 182
8.2.3 Toggle (T) Flip-Flop Memory Based on Enzyme-Catalyzed Reactions 185
8.2.4 Enzyme-Based Flip-Flop Memory Systems: Conclusions and Perspectives 186
8.3 Memristor Based on Enzyme Biocatalytic Reactions 188
8.3.1 Memristors: From Semiconductor Devices to Soft Matter and Biomolecular Materials 188
8.3.2 The Memristor Device Based on a Biofuel Cell 189
8.3.3 The Memristor Device Controlled by Logically Processed Biomolecular Signals 196
8.3.4 Enzyme-Based Memristors: Conclusions and Perspectives 198
8.4 Enzyme-Based Associative Memory Systems 198
8.4.1 Associative Memory: Biological Origin and Function 199
8.4.2 Realization of the Associative Memory with a Multienzyme Biocatalytic Cascade 201
8.4.3 Enzyme-Based Associative Memory: Challenges and Perspectives 203
8.5 Enzyme-Based Memory Systems: Challenges, Perspectives, and Limitations 204
References 206
9 Arithmetic Functions Realized with Enzyme-Catalyzed Reactions 211
9.1 Molecular and Biomolecular Arithmetic Systems: Introduction and Motivation 211
9.2 Half-Adder 212
9.3 Half-Subtractor 216
9.4 Conclusions and Perspectives 219
References 219
10 Information Security Applications Based on Enzyme Logic Systems 223
10.1 Keypad Lock Devices as Examples of Electronic Information Security Systems 223
10.2 Keypad Lock Systems Based on Biocatalytic Cascades 224
10.3 Other Biomolecular Information Security Systems 229
10.3.1 Steganography and EncryptionMethods Based on Bioaffinity Complex Formation Followed by a Biocatalytic Reaction 229
10.3.2 Barcodes Produced by Bioelectrocatalytic Reactions 231
10.4 Summary 233
References 233
11 Enzyme Logic Digital Biosensors for Biomedical, Forensic, and Security Applications 235
11.1 Introduction: Short Overview 235
11.2 From Traditional Analog Biosensors to Novel Binary Biosensors Based on the Biocomputing Concept 235
11.3 How Binary Operating Biosensors Can Benefit Biomedical Analysis: Requirements, Challenges, and First Applications 238
11.4 Binary (YES/NO) Analysis of Liver Injury Biomarkers: From Test Tube Probes to Animal Research 240
11.5 Further Examples of Injury Biomarker Analysis Using AND/NAND Logic Gates 245
11.5.1 Soft Tissue Injury (STI) Logic Analysis 246
11.5.2 Traumatic Brain Injury (TBI) Logic Analysis 247
11.5.3 Abdominal Trauma (ABT) Logic Analysis 250
11.5.4 Hemorrhagic Shock (HS) Logic Analysis 251
11.5.5 Oxidative Stress (OS) Logic Analysis 254
11.5.6 Radiation Injury (RI) Logic Analysis 258
11.6 Multienzyme Logic Network Architectures for Assessing Injuries: Aiming at the Increased Complexity of the Biocomputing–Bioanalytic Systems 261
11.6.1 The System Structure Based on the Complex Biocatalytic Cascade 261
11.6.2 STI Operation Mode of the Logic Network 264
11.6.3 TBI Operation Mode of the Logic Network 265
11.6.4 Switching Between the STI and TBI Modes and General Comments on the System 267
11.7 New Approach in Forensic Analysis: Biomolecular Computing-Based Analysis of Forensic Biomarkers 268
11.8 Logic Analysis of Security Threats (Explosives and Nerve Agents) Based on Biocatalytic Cascades 270
11.9 Integration of Biocatalytic Cascades with Microelectronics and Wearable Sensors 272
11.10 Conclusions and Perspectives 276
References 276
12 Release of Molecular Species Stimulated by Logically Processed Biomolecule Signals 283
12.1 Motivation and Experimental Background 283
12.2 Fe3+-Cross-Linked Alginate Hydrogel is a Good Example of Matrix for Signal-Stimulated Release 284
12.3 DNA Release as an Example of Signal-Stimulated Biomolecule Release 287
12.4 Bioelectrochemical Systems with Sensing and Releasing Electrodes 287
12.4.1 Sensing Electrodes Activated with Single Input Identity Gate 288
12.4.2 Sensing Electrodes Activated with Multi-input Logic Networks 288
12.4.3 Releasing Electrodes: Various Released Species for Different Applications 291
12.5 Fe3+-Cross-Linked Alginate Hydrogel Decomposition and Entrapped Molecule Release Triggered by Enzymatically Produced H2O2 294
12.5.1 DNA Release from Fe3+-Cross-Linked Alginate Hydrogel Stimulated by Signals Processed through OR, AND, and INHIB Logic Gates 294
12.5.2 DNA Release from Fe3+-Cross-Linked Alginate Hydrogel Stimulated by Signals Processed Through Multi-gate Network Composed of Concatenated AND Gates 304
12.6 Conclusions and Perspectives 307
References 307
13 Biofuel Cells Controlled by Biocomputing Systems 313
13.1 Introduction: Biofuel Cells,Their Applications, and Motivation for Designing Adaptive, Signal-Controlled Devices 313
13.2 Biofuel Cells Controlled by Logically Processed Biochemical Signals 315
13.3 Biofuel Cells Controlled by Biomolecular Keypad Lock Systems 326
13.4 Conclusions and Perspectives 328
References 330
14 Bioelectronic Interface Between Enzyme-Based and DNA-Based Computing Systems 335
14.1 Introduction: Interfacing Enzyme-Based and DNA-Based Computing Systems Is a Challenging Goal 335
14.2 Bioelectronic Interface Transducing Logically Processed Signals from an Enzymatic System to a DNA System 336
14.3 The Bioelectronic Interface Connecting Enzyme-Based Reversible Logic Gates and DNA-Based Reversible Logic Gates: Realization in a Flow Device 344
14.3.1 Enzyme-Based Fredkin Gate Processing Biomolecular Signals Prior to the Bioelectronic Interface 345
14.3.2 Reversible DNA-Based Feynman Gate Activated by Signals Produced by the Enzyme-Based Fredkin Gate 348
14.4 Conclusions and Perspectives 351
References 352
15 What Is Next? Mimicking Natural Biological Information Processes 357
15.1 Motivation and Goals 357
15.2 Example and Discussion of Feed Forward Loops 358
15.3 Enzymatic Feed-Forward Loops 360
15.4 Process Design and Kinetic Modeling 364
15.5 Simpler Biocatalytic Systems: Not a Feed-Forward Loop Yet 366
15.6 Conclusion 367
References 368
16 Conclusions and Perspectives: Where Are We Going? 371
16.1 Conclusions 371
16.2 Perspectives 373
16.2.1 Information Processing Through Complex Biological Pathways in Cells 374
16.2.2 Signal-Controlled Bioelectronic Devices and Signal-Triggered Molecular Release 375
16.2.3 Allosteric and Hybrid Enzymes 375
16.2.4 Enzyme System Controlled by Various Chemical and Physical Signals 377
16.2.5 Molecular and Nanomachines for Self-Propulsion and Logic Operation 378
16.3 Final Comments 379
References 380
Index 383
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