New public database of AI-predicted protein structures could transform biology

New public database of AI-predicted protein structures could transform biology

New public database of AI-predicted protein structures could transform biology Last week, two groups unveiled the culmination of years of work by computer scientists, biologists, and physicists: advanced modeling programs that can predict the precise 3D atomic structures of proteins and some molecular complexes. And now, the biggest payoff of that work has arrived. One of those teams reports today it has used its newly minted artificial intelligence (AI) programs to solve the structures of 350,000 proteins from humans and 20 model organisms, such as Escherichia coli bacteria, yeast, and fruit flies, all mainstays of biological research. In the coming months, the group says it plans to expand its list of modeled proteins to cover all cataloged proteins, some 100 million molecules. “It’s pretty overwhelming,” says John Moult, a protein folding expert at the University of Maryland, Shady Grove, who runs a biennial competition called the Critical Assessment of protein Structure Prediction (CASP). Moult says structural biologists have dreamed for decades that accurate computer models would one day augment extremely precise protein shapes derived from experimental methods such as x-ray …
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