🔥 Through AlphaFolds Limits to Predict How Proteins Change
Published by OOPSONLINE.IN · Source: Phys.org · 1 min read · · Updated
What actually happened
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.
Key points
- 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.
Summary based on data provided by Phys.org. Full article available at the original publisher.
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