Chemists soon could be able to “program” how DNA molecules interact in a test tube or cell, thanks to a new computer language.
A team led by the University of Washington (UW) has developed a programming language for chemistry that it hopes will streamline efforts to design a network that can guide the behaviour of chemical-reaction mixtures in the same way that embedded electronic controllers guide cars, robots and other devices.
To design the tool the UW engineers took chemical reaction networks, a century-old language of equations that describes how mixtures of chemicals behave, and used them to write programs that direct the movement of tailor-made molecules.
“We start from an abstract, mathematical description of a chemical system, and then use DNA to build the molecules that realize the desired dynamics,” said corresponding author Georg Seelig, a UW assistant professor of electrical engineering and of computer science and engineering.
“The vision is that eventually, you can use this technology to build general-purpose tools.”
Currently, when a biologist or chemist makes a certain type of molecular network, the engineering process is complex, cumbersome and hard to repurpose for building other systems.
The UW team wanted to create a framework that gives scientists more flexibility and Seelig likens this new approach, published in journal Nature Nanotechnology, to programming languages that tell a computer what to do.
“I think this is appealing because it allows you to solve more than one problem,” Seelig said. “If you want a computer to do something else, you just reprogram it. This project is very similar in that we can tell chemistry what to do.”
Humans and other organisms already have complex networks of nano-sized molecules that help to regulate cells and keep the body in check.
But scientists are now finding ways to design synthetic systems that behave like biological ones with the hope that synthetic molecules could support the body’s natural functions,but a system is needed to create synthetic DNA molecules that vary according to their specific functions.
While the new approach is not ready to be applied in the medical field, but future uses could include using this framework to make molecules that self-assemble within cells and serve as “smart” sensors.
These could be embedded in a cell, then programmed to detect abnormalities and respond as needed, perhaps by delivering drugs directly to those cells.
Seelig and colleague Eric Klavins, a UW associate professor of electrical engineering, recently received $2m (£1.2m) from the US National Science Foundation as part of a national initiative to boost research in molecular programming. The new language will be used to support that larger initiative, Seelig said.