A natural language model has jumpstarted the process of protein design by creating active enzymes. Researchers have developed an AI system that can generate artificial enzymes from scratch. In laboratory experiments, some of these enzymes demonstrated efficacy comparable to natural enzymes, even wh
According to the researchers, this new technology has the potential to surpass directed evolution and could energize the field of protein engineering by hastening the creation of new proteins for various purposes, such as therapeutics and plastic degradation.Researchers have developed an AI system that can generate artificial enzymes from scratch.
“The language model is learning aspects of evolution, but it’s different than the normal evolutionary process,” Fraser said. “We now have the ability to tune the generation of these properties for specific effects. For example, an enzyme that’s incredibly thermostable or likes acidic environments or won’t interact with other proteins.”
Out of this first batch of a 100 proteins, which were screened in vitro by Tierra Biosciences, the team made five artificial proteins to test in cells and compared their activity to an enzyme found in the whites of chicken eggs, known as hen egg white lysozyme . Similar lysozymes are found in human tears, saliva, and milk, where they defend against bacteria and fungi.
The AI was even able to learn how the enzymes should be shaped, simply from studying the raw sequence data. Measured with X-ray crystallography, the atomic structures of the artificial proteins looked just as they should, although the sequences were like nothing seen before. “When you train sequence-based models with lots of data, they are really powerful in learning structure and rules,” said Nikhil Naik, Ph.D., Director of AI Research at Salesforce Research, and the senior author of the paper. “They learn what words can co-occur, and also compositionality.”
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