KAIST unveils homegrown AI model for predicting protein structures, drug binding
Researchers at the Korea Advanced Institute of Science and Technology (KAIST) said Friday they have developed a biomolecular artificial intelligence (AI) model, called K-Fold, that predicts protein structures and how drug candidates bind to them, with the aim of speeding up new drug development using homegrown technology. The model was built by a KAIST-led group called Team KAIST as part of a…
KAIST researchers have unveiled an AI model named K-Fold designed to predict protein structures and drug binding, aiming to accelerate the development of new medications. The model was created by a KAIST-led team as part of a project funded by the Korean Ministry of Science and ICT. KAIST President Bae Chung-sik highlighted the significance of "sovereign AI" for national competitiveness in the AI era.
K-Fold is capable of predicting not only the three-dimensional shape of a single protein but also its interactions with other proteins, drug candidates, and genetic material like DNA and RNA. The model's ability to predict drug binding is crucial in early-stage drug discovery, where researchers must identify disease-related proteins targets.
Written by urgent.news from The Korea Times's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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