Shaped like dogs, stars, and the Mona Lisa, you could mistake these DNA structures for fun-shaped macaroni if they weren’t only nanometers wide. South Korean scientists made the constructions using a technique called DNA origami that can bend genetic material into any form. Designing DNA strands so they’ll fold into a specific shape typically requires tedious manual work, but the researchers behind the playful fabrications have developed a shortcut using generative AI.
The AI model, called Generative SNUPI (short for Structured Nucleic Acids Programming Interface, and yes, inspired by the dog), was created by research teams at Seoul National University (SNU) and Hanyang University. The work behind it, which was accepted for publication in Nature Communications* , *shows the model can conjure DNA origami designs that work in the real world for user-requested shapes. For a design like the Mona Lisa, that doesn’t mean simply tracing an outline; the model considers the chemical rules of DNA to tell researchers how unpaired DNA strands should be sequenced so that molecular forces will cause them to self-contort into the required shape.
DNA origami techniques have been around for two decades now, with potential applications ranging from nanoscale robots to therapeutic structures that interact with cells. But these innovations have been slowed by how time-consuming and expensive the DNA structure design process can be.
“Traditionally we need some expertise, background knowledge, and know-how to design the proper nanostructures that we intend to make,” says Kyounghwa Jeon, a PhD candidate at SNU. The work requires humans running algorithms and tweaking results until the desired shape is achieved and structurally stable. With Generative SNUPI, she says, users could, in theory, go straight from drawing a target shape to physically assembling the DNA.
Rebecca Taylor, a professor of mechanical engineering at Carnegie Mellon University who was not involved in the research, says the new generative platform is exciting for researchers. “The entire field is sort of enabled and held back by its tools. When you make a new tool that enables a new tech, a new capability, that’s just such a big advance for the field.”
Generative SNUPI designs DNA sequences that, when synthesized, fold into nanoscale replicas of user-requested shapes.Source images: Chien Truong-Quoc, Kyounghwa Jeon, et al.
Designing DNA origami using Generative SNUPI begins with a target shape. That could be something with complex curvature, like the outline of a dog’s face, or a more simple geometric pattern. Next, the new tech comes into play: Generative SNUPI applies a diffusion model, which adds and refines noise to the input shape to create the desired output in DNA form. Diffusion models are how platforms like DALL-E and Midjourney create AI-generated imagery.
“What it looks like is one of those kids crafts where you decorate something with glue and then put glitter all over it,” says Taylor. When the noise is removed—or, the glitter is shaken off—the design is revealed. “They’re basically just saying ‘populate this guide that I have with the DNA,’ but they also know how DNA comes together … that’s the thing that it’s really been trained on.”
The arts-and-crafts metaphors only continue once Generative SNUPI returns the DNA sequences that form the target shape. Scientists chemically synthesize short DNA strands called staples and used biological methods to produce a long strand called a scaffold. The staples pull the scaffold into shape in a way that Jeon says is “very similar to stapling paper.” The staple-scaffold relationship exploits DNA’s imperative to bond guanine to cytosine and adenine to thymine; the exact positions of each of these molecule are dictated by Generative SNUPI during the design process.
Researchers were able to produce a variety of DNA origami structures, but some did not hold their shape at first, notes Do-Nyun Kim, an assistant professor of mechanical engineering at SNU. “This occurred not because Generative SNUPI had an error, but because the drawn shape was, in fact, structurally unstable,” he says. In response, they added a step before actually designing the DNA sequence to predict the structural integrity of the input shape.
To expand Generative SNUPI’s capacity for real world applications, Kim says that DNA origami designs will need to be less rigid than what the model is currently able to produce. The technology reaching its full potential could mean life-saving uses like drug delivery and immunotherapy, but these uses often require flexibility.
“Most molecular structures are dynamic and reconfigure in response to external stimuli to perform their designated functions,” he says. “So, we plan to extend the current work to the design of dynamically reconfigurable structures in future research.”