When a protein folds, its string of amino acids wiggles and jiggles through countless conformations before it forms a fully folded, functional protein. This rapid and complex process is hard to ...

Today (September 21), the Lasker Foundation announced this year’s award winners. John Jumper, a computational biologist at DeepMind, and Demis Hassabis, cofounder and CEO at DeepMind, were awarded the ...

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 ...

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 ...

This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...

Researchers from Cleveland Clinic and IBM recently published findings in the Journal of Chemical Theory and Computation that could lay the groundwork for applying quantum computing methods to protein ...

The “ChatGPT moment” for biology proceeds to unfold as protein language models, or machine learning tools trained on large databases of protein sequences, work to decode the language of life with the ...

It has long been thought that protein function and stability are highly sensitive to changes in the composition of the internal structures, or protein cores. However, a large-scale experiment probing ...

For most proteins, structure is function. The complex three-dimensional shapes that proteins adopt create folds and pockets that can accomplish the remarkably improbable: driving chemical reactions ...