A team of bioengineers and synthetic biologists has developed a computational workflow that can design thousands of new enzymes, predict their behavior in the real world, and test their performance across multiple chemical reactions, all on a computer. This breakthrough could revolutionize the enzyme engineering field, which is crucial for many industries, including pharmaceuticals, energy, and the environment. Traditionally, scientists would use living cells to produce enzymes, a process that is time-consuming and costly. With this new approach, scientists can use machine learning to predict the performance of enzymes and test them quickly, potentially reducing the time and cost of enzyme development. The team’s proof-of-concept study demonstrated the success of their approach, synthesizing a small-molecule pharmaceutical at 90% yield, compared to an initial 10% yield. The potential applications of this technology are vast, including the development of new enzymes for sustainable energy, cleaner air and water, and more efficient pharmaceuticals. While there are still some challenges to overcome, this breakthrough has the potential to accelerate the discovery of new enzymes and improve the efficiency of many industries.
AI Pioneers Break New Ground in Enzyme Discovery, Spearheading a New Era in Research
