Visions of DNA Nanotechnology at 40 for the Next 40: A Tribute to Nadrian C. Seeman

In Memoriam
Preface
Contents
Perspectives
Beyond Watson-Crick: The Next 40 Years of Semantomorphic Science
1 A Brief Retrospective
2 A Science Allegory
3 A Roadmap
3.1 DNA Semantics: Schrödinger Crystals Versus Seeman Crystals
3.2 DNA Syntax—Information Bundles and Secondary Structures
3.3 Nucleic Acid Operating Systems: XNA and Beyond
4 Beyond Watson-Crick: A Call to Action
References
DNA Nanotechnology Out of Equilibrium
1 DNA Nanotechnology: A Personal Account
2 Designing and Programming with DNA
2.1 DNA—A Programmable Molecule
2.2 Learning by Building
2.3 Challenges and Limitations
3 From Self-Assembly to Non-equilibrium Dynamics and Self-Organization
3.1 Molecular Machines
3.2 Non-equilibrium Chemical Dynamics and Self-Assembly
3.3 Robots
4 What Lies Ahead?
References
The Evolution of DNA-Based Molecular Computing
1 A Brief History of DNA Computing
2 Opportunities and Challenges
2.1 Bridge Between Matter and Information
2.2 Massive Parallelism
2.3 Scalability
3 Directions for Future Development and Potential Approaches
3.1 Scaling-Up
3.2 Updating and Reusing
4 Summary
References
DNA Nanotechnology Research in Japan
1 Introduction
2 How the Author Got Involved in DNA Nanotechnology
3 The Evolution of Projects in Japan
3.1 The 1980s and 1990s
3.2 The 2000s
3.3 The 2010s
3.4 Current Research
4 Summary
References
Reminiscences from the Trenches: The Early Years of DNA Nanotech
1 Discovering DNA Computing
2 Connections to Broader Scientific Themes
3 Ned Seeman: Founder of the Field
4 Personal Milestones
5 The End of the Early years
References
Chemistry and Physics
Beyond DNA: New Digital Polymers
1 New Polymer 1 (NP1)
2 New Polymer 2 (NP2)
3 New Polymer 3 (NP3)
4 Example Applications
5 Conclusions
References
Controlling Single Molecule Conjugated Oligomers and Polymers with DNA
1 Modular Self-Assembly of Molecular Components
2 Conjugated Polymers on DNA Origami
3 Work from Other Groups
4 Conclusion
References
Organizing Charge Flow with DNA
1 Origami’s Rise
2 Making DNA Nanostructures Conductive Through Metallization
3 Decorating Origami
3.1 DNA Scaffolding for Conductive Metals
3.2 DNA Scaffolds for Conductive Polymers
3.3 DNA Scaffolds for Carbon Nanotubes
3.4 Highly Ordered, Three-Dimensional DNA-CNT Arrays
4 The Future of DNA-Organized Electronics
4.1 Making DNA More Electronic
4.2 Scaffolding Biocompatible Electronic Materials
References
DNA Assembly of Dye Aggregates—A Possible Path to Quantum Computing
1 Introduction
2 The Mathematical Structure of Reality
3 Quantum Computers
3.1 The Controlled NOT Gate
3.2 Quantum Parallelism
4 The Frenkel Exciton Hamiltonian
5 Energy Eigenvalues of a Homodimer Dye Aggregate and Davydov Splitting
6 Coherent Exciton Hopping
7 Exciton Transmission Lines
8 Representation of an Exciton Qubit
9 Basis Change Gates
10 Phase Gates
11 An Exciton Interferometer
12 A Controlled Phase Shift
13 A CNOT Gate
14 Exciton-Based Quantum Computer Architecture
15 But Isn't a Quantum Computer Just an Analog Computer?
16 Molecular Vibrations
17 Conclusion
References
Structures
Building with DNA: From Curiosity-Driven Research to Practice
1 Introduction
2 Engineering Cell-Sized DNA Structures
2.1 Challenges
2.2 Opportunities
3 Building Designer DNA Crystals with Atomic Resolutions
3.1 Challenges
3.2 Opportunities
4 Transferring to RNA Structural Design
4.1 Challenges
4.2 Opportunities
5 At the End
References
From Molecules to Mathematics
1 Introduction
2 Flexible Tiles and New Graph Invariants
3 DNA Strand Routing and Topological Graph Theory
4 DNA Origami and New Algebraic Structures
5 DNA Origami and Origami Knots
6 Where Next?
References
Origami Life
1 Origami Molecules
2 Origami Design Algorithms
3 Origami Folding Pathways
4 Folded Origins
References
Ok: A Kinetic Model for Locally Reconfigurable Molecular Systems
1 Introduction
2 Molecular Reconfiguration: Oritatami and Nubots
3 The Ok model
3.1 Reconfiguration Events
3.2 Reconfiguration Distributions and Events Rates
3.3 Implementing the Ok model
4 Conclusion
References
Implementing a Theoretician's Toolkit for Self-Assembly with DNA Components
1 Introduction
2 Definitions and Notation
3 Metrics
4 Monomer Reuse: Hard-Coded Versus Algorithmic
5 Inputs
5.1 Seed Assemblies
5.2 Tile Subsets
5.3 Monomer Concentrations
5.4 Programmed Temperature Fluctuations
5.5 Staged Assembly
6 Dynamics
6.1 Cooperativity
6.2 Single Tile or Hierarchical Growth
6.3 Activatable/Deactivatable Glues
6.4 Tile Removal and Breaking of Assemblies
6.5 Reconfiguration Via Flexibility
6.6 Assembly Growth Controlled by CRNs
7 Conclusion
References
Reasoning As If
1 Introduction
2 The Snapshot Algorithm
3 Local Determinism
4 The Future of As If
References
Biochemical Circuits
Scaling Up DNA Computing with Array-Based Synthesis and High-Throughput Sequencing
1 Introduction
1.1 Scaling up DNA Computing for Molecular Diagnostics
1.2 Scaling up DNA Computing for DNA Data Storage
1.3 Limitations of Current Approaches to DNA Computing
2 A Vision for the Future
3 Results
3.1 Nicked Double-Stranded DNA Gates Reaction Mechanism
3.2 Gate Design
3.3 Making ndsDNA Gates from Array-Synthesized DNA
3.4 Characterizing Gate Kinetics
3.5 Reading Out DNA Computation with Next-Generation DNA Sequencing
3.6 Reading Pools of Array-Derived Gates
4 Discussion
References
Sequenceable Event Recorders
1 Introduction
2 Occurrence Recorder
2.1 Yes Gate
2.2 Occurrence Recorder Algorithm
3 Coincidence Recorder
3.1 Join Gate
3.2 Coincidence Recorder Algorithm
4 Preorder Recorder
4.1 Choice Gate Specification
4.2 Preorder Recorder Algorithm
4.3 Crosstalking Choice Gate
4.4 A ``Proper'' Choice Gate
5 Conclusions
References
Computational Design of Nucleic Acid Circuits: Past, Present, and Future
1 Past
1.1 Visual DSD Origins
1.2 Visual DSD Evolution
1.3 Visual DSD Analysis
2 Present
2.1 Logic Programming Framework
2.2 Related Work
3 Future
3.1 Computational Tool Integration
3.2 Experiment Integration
3.3 Computational Design for Practical Applications
References
Spatial Systems
Parallel Computations with DNA-Encoded Chemical Reaction Networks
1 Harnessing Parallelization in Chemical Reaction Networks
1.1 D(R)NA-Based Deterministic Chemical Reaction Networks
1.2 CRNs Run on Inherently Parallel Processes
2 Creating Sub-Computations
2.1 No-Diffusion (Leak–Tight) Compartments
2.2 Compartment-Free Approaches
2.3 Intermediate Cases: Some Species Diffuse, Some Do Not
3 Discussion and Applications
3.1 Independent Compartments Containing an Identical Circuit but Receiving Different Inputs
3.2 Independent Compartments Containing Different Circuits, All Working on the Same Inputs
3.3 Cross-Talking Compartments Collaborating to Compute a Global Response
References
Social DNA Nanorobots
1 Introduction
1.1 Motivation
1.2 Summary of Our Results
1.3 Organization
2 Sociobiology
3 Prior DNA Nanorobots
3.1 Prior DNA Walkers
3.2 Prior Programmable DNA Nanorobots
3.3 Prior Autonomous DNA Walkers that Do Molecular Cargo-Sorting on a 2D Nanostructure
4 Design and Simulation of Social DNA Nanorobots
4.1 Social DNA Nanorobot Behaviors Designed and Simulated
4.2 Software for Stochastic Simulations of the Social DNA Nanorobots Behaviors
4.3 A Prior DNA Nanorobot that Autonomously Walks
4.4 Prior Demonstrated Technique for Hybridization Inhibition of Short Sequences Within the Hairpin Loops
4.5 A Novel DNA Nanorobot that Executes a Self-Avoiding Walk
4.6 Flocking: Novel DNA Nanorobots that Follow a Leader
4.7 Novel DNA Nanorobots that Vote by Assassination
5 Discussion
5.1 Further Development of Simulation Software for Social Nanorobots
5.2 Experimental Demonstrations of Social DNA Nanorobots
5.3 Further Social DNA Nanorobot Behaviors
5.4 Communication Between Distant Social Nanorobots
References
Models of Gellular Automata
1 Introduction: Why Cellular Automata?
1.1 Computation by Molecules
1.2 Smart Materials
1.3 Why Discrete?
2 Implementation of Cellular Automata
2.1 Molecular Level
2.2 Reaction–Diffusion Systems
3 Gellular Automata
3.1 Gellular Automata with Holes
3.2 Boolean Total and Non-Camouflage Gellular Automata
3.3 Three-Dimensional Gellular Automata That Learn Boolean Circuits
4 Supervised Learning of Boolean Circuits
4.1 Assumption
4.2 States
4.3 Algorithm
5 Concluding Remark
References
Patterning DNA Origami on Membranes Through Protein Self-Organization
1 Introduction
2 DNA Origami as a Tool to Elucidate Molecular Mechanisms
3 Stable DNA Origami Patterns on Lipid Membranes
4 Challenges and Opportunities
5 Materials and Methods
References