Research

What is molecular programming?

Molecular programming is a term for a broad area of science which studies and engineers the encoding and processing of information at the molecular scale. This means pulling diverse research and concepts from many fields, including biology, chemistry, physics, computer science, and information/complex systems theory. I work on implementations of molecular programs using nucleic acids, but alternative approaches are also possible using proteins or even solutions of small molecules. Theoretical areas in the field include:

• Fundamental theory of self-assembly
• Abstracting computation as theoretical chemical reaction networks
• Compilation of theoretical information processing schemes into real molecules

Which leads to technological capabilities using nucleic acids as building blocks such as:

• Nanoscale engineering with nucleic acid nanotechnology
• Complex diagnostics and combinatorial computing with toehold-mediated strand displacement
• DNA data storage and retrieval

We are at an exciting time in the development of Molecular Programming. The field has realized a variety of composable, programmable molecular systems which can be employed in diverse areas such as complex diagnostics and nanoscale photonics. Watch this space for breakthroughs in scale, integration and robustness, which enable new frontiers in nanotechnology. If you want to learn more about the field, check out the website of our professional society, ISNSCE

My research

Our ability to build complex, nanoscale structures out of nucleic acids depends both on our understanding of material properties at the nanoscale, particularly flexibility, and our ability to design molecular contacts to control said flexibility. By using physics-based simulations, we can diagnose problems with designs and build more precise molecular interfaces.

My research focuses on building bridges between physics- and data-based molecular modeling and wet-lab implementation of nucleic acid nanostructures. Using molecular models, I have worked with my experimental colleagues to, characterize flexibility, identify failure modes, and refine designs. This requires me to be well-versed in both experimental and computational methods and to effectively communicate to specialists in both areas.

I am particularly interested in RNA structure. The RNA nanotechnology field started by composing natural RNA motifs, which have intricate 3D architectures, into designed nanostructures. These days, we have moved away from that paradigm towards toward design techniques which more resembles DNA origami—structures made up of canonical base-pairs and holiday junctions. However, this comes at a cost of precision and flexibility. Compared with natural RNA structures, such as the ribosome, our RNA nanostructures are crude, imprecise, and flexible. Using computational models, I hope to enable the next generation of RNA structures which combine the scalability of RNA origami, with the precise atomic arrangement of natural RNA.