[Press Release] Breaking through AlphaFold’s limits to predict how proteins change shape
AlphaFold3 diffusion model (A) Conformational sampling by the diffusion generative model of AlphaFold3. (B) The method developed in this study enhances conformational sampling with AlphaFold3 by introducing a bias.
(Credit: Jun Ohnuki and Kei-ichi Okazaki, Institute for Molecular Science, Restriction: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only.)
Release Summary
Conformational changes in proteins are vital to their function yet remain challenging for state-of-the-art artificial intelligence, such as AlphaFold3, to predict. Researchers at the Institute for Molecular Science (IMS), and the Graduate University for Advanced Studies, SOKENDAI introduced a repulsive force between predicted structures, allowing AlphaFold3 to sample the multiple conformational states that its default settings rarely capture.
