Periodic Reporting for period 3 - Active-DNA (Computationally Active DNA Nanostructures)
Okres sprawozdawczy: 2021-11-01 do 2023-04-30
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. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute “wet” nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, 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.
This project, Active-DNA, aims to address this challenge by achieving 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 carry out complex programmable tasks and (3) self-replicating DNA nanocomputers whose stored programs undergo evolution. Active-DNA research will range from defining models and proving theorems that characterise the computational and expressive capabilities of such 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.
This project, Active-DNA, aims to address this challenge by achieving 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 carry out complex programmable tasks and (3) self-replicating DNA nanocomputers whose stored programs undergo evolution. Active-DNA research will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.
Work is progressing with exciting progress on a number of fronts. A number of DNA tile motif designs have been elaborated and road-tested for our first objective, and we expect to go beyond original plans by realising this objective in several distinct ways. We have published theoretical conference papers (one at STOC 2020, another at DNA27) for our first objective, and for some time now have primarily focused on experimental work. For our second objective, we have developed a new theoretical model of molecular robotics called Turning Machines (published at the DNA26 conference), and have developed initial designs to implement that model. The model is intentionally designed to have rudimentary computational abilities, yet be capable of folding a wide class of 2D shapes. For our third objective, to create self-replicating DNA nanocomputers, we have developed a novel design that significantly simplifies previous approach and performs well in tests.
The proposal aims us to take the next step forward in control of the dynamics of molecules at the nanoscale. We are taking ideas from computation, and from the theory of molecular computing in particular, and applying that to DNA nanoscale engineering. This has the potential to change how we think about two topics. Firstly, for molecular computing by clarifying what molecular motifs are feasible and which parts of theory are most relevant. Secondly, for tile-based self-assembly by focusing attention on making the shift from structure-based engineering to dynamics-based engineering as an enabler of higher yield and more complex nanostructures.