Diverse and robust molecular algorithms using reprogrammable DNA self-assembly

Area of Science:

• Molecular nanotechnology
• Information-based chemistry
• Algorithmic self-assembly

Background:

• Molecular biology demonstrates chemical systems' capacity for information storage and processing.
• Algorithmic behavior can be embedded in molecular self-assembly, experimentally shown with DNA nanotechnology.
• A complexity threshold exists for information technologies, previously unaddressed in DNA self-assembly.

Purpose of the Study:

• To investigate if DNA self-assembly can exceed the complexity threshold for programmable systems.
• To design and validate a DNA tile set capable of executing diverse algorithms.

Main Methods:

• Designed a DNA tile set comprising 355 single-stranded tiles.
• Experimentally validated the tile set by reprogramming it to implement various 6-bit algorithms.
• Constructed 21 distinct DNA circuits to execute algorithms with high fidelity.

Main Results:

• Successfully reprogrammed the DNA tile set to implement a wide range of 6-bit algorithms.
• Demonstrated execution of algorithms including copying, sorting, pattern generation, and computation.
• Achieved a low per-tile error rate of less than 1 in 3,000.

Conclusions:

• Molecular self-assembly can serve as a reliable component in programmable chemical systems.
• The developed system suggests the feasibility of exceeding the complexity threshold in molecular computation.
• Enables a new creative space for molecular programmers to develop advanced molecular machines.