Chemical & Engineering News has reported on the recent surge in genetive AI for protein design.
In the past year, phrases like learned language models, diffusion, and hallucination have gained new meanings in popular culture as artificial intelligence has started taking over mundane tasks. Today, users can log on to an AI-powered chatbot and ask it to draft texts based on simple prompts. They can then use text-to-image services to create illustrations and new images to accompany the dreamed-up words.
But beyond these consumer applications, algorithmic approaches are helping researchers create a whole world of new proteins—proteins that could become vaccines, biologic therapies, materials, or tools for bioremediation.
A few years ago, C&EN chatted with David Baker of the University of Washington about a host of topics, including de novo protein design, which is designing new proteins from scratch rather than adjusting existing ones. Back then, he said he tried not to look too far into the future. Too much could change; too much was uncertain. That has never been truer.
Image by C&EN; Adapted from Comput. Struct. Biotechnol. J./Yang H. Ku/C&EN/Shutterstock
De novo protein design has reached an inflection point, researchers say. AI-powered protein design is becoming very real and very usable, thanks to technological advances in the development of algorithms and the hardware that runs them.
Protein science itself was uniquely positioned to take advantage of these advances because of the enormous amounts of work carried out over the past 50 years to curate and annotate biological data.
“Every time there is a new method in computer vision or natural language processing, we are in a race to try to transfer it to biology,” says protein designer Noelia Ferruz at the Institute of Molecular Biology of Barcelona. “I guess it’s the perfect moment, because we’re seeing an AI revolution in every field.”
Read more at cen.acs.org