Chemical computer can recognise patterns and perform multiple tasks

A chemical computer built from a network of enzymes can perform various tasks, such as measuring temperature or identifying substances, without having to rebuild it every time. This makes it more like an adaptive biological system than a digital circuit, and promises to link computers to biology.

Living organisms contain molecular networks that constantly integrate chemical and physical signals, such as when cells sense nutrients, hormones, or temperature changes and adapt to stay alive. For decades, researchers have tried to imitate this in various ways, such as by creating logic gates from DNA, but most of these artificial systems were either too simple, too rigid, or too difficult to scale up.

Now, Wilhelm Hook at Radboud University in the Netherlands and colleagues took a different approach. Instead of programming each chemical step, they created a system in which enzymes interact freely, creating complex behavior that makes it possible to learn to recognize patterns in chemical actions.

The team's computer uses seven different types of enzymes loaded into tiny hydrogel beads packaged in a small tube. Through this tube flows a liquid into which short chains of amino acids called peptides can be injected, which serve as “input” to the computer. As peptides pass through enzymes, each enzyme naturally tries to cut them at specific locations along the peptide chain. But once one enzyme makes a cut, the shape of the peptide and the available cutting sites change, which can either open up or block opportunities for other enzymes.

Because one reaction can flow into another, enzymes create an ever-changing chemical network, creating characteristic patterns that the system can interpret. “We can think of enzymes as…hardware and peptides as software. [that] solves new problems depending on the input data,” says Dongyang Li from Caltech, who was not involved in the work.

For example, temperature affects the speed of each enzyme; at higher temperatures, some enzymes are accelerated more than others, changing the mixture of peptide fragments at the system's output. By analyzing these peptide fragments using a machine learning algorithm, the researchers were able to associate these fragments with specific temperatures.

Because different chemical reactions occur on different time scales, the system naturally retains a kind of “memory” of past signals, allowing it to recognize patterns that unfold over time. For example, it can detect the difference between fast and slow pulses of light, meaning it doesn't just respond to input signals, but tracks how they change.

The result is not a static chemical circuit, but rather a dynamic, multitasking chemical computer that processes signals like a living system. “The same network solved many problems—chemical classification, temperature measurement with an average error of ~1.3°C in the range of 25–55°C, pH classification, and even responding to the frequency of light pulses—without changing the chemical composition,” says Li.

The researchers were surprised at how well the computer worked given its small size, and Hack hopes that one day a more advanced system could be used to translate optical or electrical signals directly into chemical signals, allowing it to respond in the same way that living cells do. “We only used six or seven enzymes and six peptides,” he says. “Imagine what you could do with a hundred enzymes.”