Coarse-grained model simulates DNA-RNA hybrids for biological research, nanoengineering

Nucleic acids are incredibly useful molecules, as evidenced by our reliance on DNA to encode genetic information and RNA to synthesize proteins. Many nanotechnological applications, such as drug delivery, vaccines, and gene editing, depend on DNA, RNA, or increasingly, a hybrid of both. As a result, the ability to accurately simulate the behavior of DNA-RNA hybrids is crucial for advancing these technologies.

Ratajczyk et al. developed a coarse-grained computational model for simulating DNA-RNA hybrids. This model, named oxNA, enables researchers to study larger systems over longer timescales than atomistic simulations.

“The field of nucleic acid nanotechnology has already started to develop hybrid nanostructures, typically using RNA as a scaffold and shorter DNA strands as staples,” said author Ard Louis. “There was a growing need for a new computational tool to guide corresponding experimental efforts.”

OxNA is based on existing models that simulate DNA and RNA separately. The authors demonstrated the potential of oxNA to simulate common hybrid structures such as R-loops, toehold-mediated strand displacement reactions, and RNA-scaffolded wireframe origami nanostructures. It can also help when studying other DNA-RNA interactions like DNA transcription and replication.

The team believes their work will help researchers looking to better understand existing biological hybrid structures as well as groups engineering new nucleic acid structures. They plan to employ their model to further their own research, too.

“We want to use the model to study hybrid DNA-RNA nanostructures by looking at their flexibility and mean structure, as well as using simulations to rationalize their assembly yield and successful function as observed in experiments,” said Louis.

Source: “Coarse-grained modelling of DNA-RNA hybrids,” by Eryk J. Ratajczyk, Petr Sulc, Andrew Turberfield, Jonathan Doye, and Ard A. Louis, Journal of Chemical Physics (2024). The article can be accessed at https://doi.org/10.1063/5.0199558 .