Periodic Reporting for period 4 - Active-DNA (Computationally Active DNA Nanostructures)
Reporting period: 2023-05-01 to 2024-10-31
During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. The workflow includes proposing theoretical models, mathematical characterisation of computational power, molecular design, physical modelling, and implementation in the wet-lab.
The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems.
The Active-DNA project tackled this challenge under three objectives: (1) design of DNA nanostructures programmed to implement any 2D or 3D self-assembly growth process, (2) robotic DNA nanostructures that compute, move and reconfigure into complex programmable shapes and (3) steps towards building self-replicating DNA nanocomputers whose stored programs undergo evolution. Active-DNA research ranged from defining mathematical models of computation, and proving theorems that characterise the computational and expressive capabilities of active programmable materials, to experimental work implementing active DNA nanostructures in the wet-lab.
The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems.
The Active-DNA project tackled this challenge under three objectives: (1) design of DNA nanostructures programmed to implement any 2D or 3D self-assembly growth process, (2) robotic DNA nanostructures that compute, move and reconfigure into complex programmable shapes and (3) steps towards building self-replicating DNA nanocomputers whose stored programs undergo evolution. Active-DNA research ranged from defining mathematical models of computation, and proving theorems that characterise the computational and expressive capabilities of active programmable materials, to experimental work implementing active DNA nanostructures in the wet-lab.
The objective of controlled self-assembly growth dynamics was realised with a novel design [Evans, Doty, Woods; publication in preparation, early version presented at the DNA28 conference].
Theoretical work, published by Meunier, Regnault, Woods, at ACM STOC 2020, on the noncooperative abstract tile assembly model proved that typical forms of computation are impossible in the model, and answered the pumpabilty conjecture of Doty, Patitz, Summers [TCS 2021]. A new direction has been the development of covered core tiles for precise control of nucleation and growth [Rogers, Evans, Woods; presented at DNA28; publications in prep]. A novel model of computation, with a thorough experimental implementation and characterisation, for thermodynamically favoured computing, was presented as Stérin*, Eshra*, Woods at the DNA28 conference, and Stérin’s PhD thesis, with additional work by others in the team [Shalaby, Thachuk, Woods, DNA29, and other papers in prep].
We developed a novel theoretical Turning Machine model of molecular robotics & reconfiguration [Kostitsyna, Wood, Woods, DNA26 and J Natural Computing 2022]. PhD student Cai Wood designed and experimentally implemented several molecular robotic models directly related to Turing Machines. The designs add memory and dynamics to large-scale molecular structure reconfiguration. Work will appear in PhD thesis of Cai Wood and future publication.
Theoretical work, published by Meunier, Regnault, Woods, at ACM STOC 2020, on the noncooperative abstract tile assembly model proved that typical forms of computation are impossible in the model, and answered the pumpabilty conjecture of Doty, Patitz, Summers [TCS 2021]. A new direction has been the development of covered core tiles for precise control of nucleation and growth [Rogers, Evans, Woods; presented at DNA28; publications in prep]. A novel model of computation, with a thorough experimental implementation and characterisation, for thermodynamically favoured computing, was presented as Stérin*, Eshra*, Woods at the DNA28 conference, and Stérin’s PhD thesis, with additional work by others in the team [Shalaby, Thachuk, Woods, DNA29, and other papers in prep].
We developed a novel theoretical Turning Machine model of molecular robotics & reconfiguration [Kostitsyna, Wood, Woods, DNA26 and J Natural Computing 2022]. PhD student Cai Wood designed and experimentally implemented several molecular robotic models directly related to Turing Machines. The designs add memory and dynamics to large-scale molecular structure reconfiguration. Work will appear in PhD thesis of Cai Wood and future publication.
The project has taken next step forward in control of the dynamics of molecules at the nanoscale by taking ideas from the theory of molecular computing and applying them to DNA nanoscale engineering.
We have developed methods to control nanoscale self-assembly by implementing tile-based systems with precise control of growth order. We have invented new, and simple, techniques to modify a wide variety of DNA tile self-assembly systems to suppress unwanted nucleation of structures, while allowing growth from a seed structure. We have built reconfigurable molecular robots that act on instructions embedded in an internal memory.
We have developed methods to control nanoscale self-assembly by implementing tile-based systems with precise control of growth order. We have invented new, and simple, techniques to modify a wide variety of DNA tile self-assembly systems to suppress unwanted nucleation of structures, while allowing growth from a seed structure. We have built reconfigurable molecular robots that act on instructions embedded in an internal memory.