Artificial intelligence has solved one of biology’s most stubborn mysteries: how proteins fold into their intricate three-dimensional shapes. But as the field shifts from prediction to application, a ...

University of Missouri researchers have released the world's largest collection of protein models with quality assessment—a ...

Artificial intelligence (AI) is transforming how scientists understand proteins—these are working molecules that drive nearly every process in the human body, from cell growth and immune defense to ...

Textbooks often depict proteins in one conformation, but real life, as usual, is much messier. While some proteins have stable, unchanging structures, many others have intrinsically disordered regions ...

The shape, or structure, of proteins determines how they work, making it essential for researchers to have access to high-quality structural models. St. Jude Children's Research Hospital investigators ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Scientists have developed a new machine learning framework that has shown the potential to be more accurate at inverse protein folding than existing state-of-the-art methods. (Nanowerk News) An AI ...

This fully updated volume explores a wide array of new and state-of-the-art tools and resources for protein function prediction. Beginning with in-depth overviews of essential underlying computational ...

The most visible impact of AI seems to be in coding, but it could also be poised to disrupt other hard sciences.

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. In a study published in the journal Nature ...