Person:

Yin, Peng

Kinetically controlled isothermal growth is fundamental to biological development, yet it remains challenging to rationally design molecular systems that self-assemble isothermally into complex geometries via prescribed assembly and disassembly pathways. By exploiting the programmable chemistry of base pairing, sophisticated spatial and temporal control have been demonstrated in DNA self-assembly, but largely as separate pursuits. By integrating temporal with spatial control, here we demonstrate the “developmental” self-assembly of a DNA tetrahedron, where a prescriptive molecular program orchestrates the kinetic pathways by which DNA molecules isothermally self-assemble into a well-defined three-dimensional wireframe geometry. In this reaction, nine DNA reactants initially coexist metastably, but upon catalysis by a DNA initiator molecule, navigate 24 individually characterizable intermediate states via prescribed assembly pathways, organized both in series and in parallel, to arrive at the tetrahedral final product. In contrast to previous work on dynamic DNA nanotechnology, this developmental program coordinates growth of ringed substructures into a three-dimensional wireframe superstructure, taking a step toward the goal of kinetically controlled isothermal growth of complex three-dimensional geometries.

Dynamic DNA nanotechnology provides a promising avenue for implementing sophisticated assembly processes, mechanical behaviours, sensing and computation at the nanoscale. However, design of these systems is complex and error-prone, because the need to control the kinetic pathway of a system greatly increases the number of design constraints and possible failure modes for the system. Previous tools have automated some parts of the design workflow, but an integrated solution is lacking. Here, we present software implementing a three ‘tier’ design process: a high-level visual programming language is used to describe systems, a molecular compiler builds a DNA implementation and nucleotide sequences are generated and optimized. Additionally, our software includes tools for analysing and ‘debugging’ the designs in silico, and for importing/exporting designs to other commonly used software systems. The software we present is built on many existing pieces of software, but is integrated into a single package—accessible using a Web-based interface at http://molecular-systems.net/workbench. We hope that the deep integration between tools and the flexibility of this design process will lead to better experimental results, fewer experimental design iterations and the development of more complex DNA nanosystems.