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 project run by Korea's Ministry of Science and ICT to develop AI foundation models specialized by field.

KAIST President Bae Chung-sik said the project reflects the importance of "sovereign AI" — a country's ability to develop and control its own core technology — for national competitiveness in the AI era.

K-Fold is designed to predict not only the 3D shape of a single protein, but also how it interacts with other proteins, drug candidates, or genetic material such as DNA and RNA, and where and how a candidate compound binds.

That combination of structure prediction and binding prediction is central to early-stage drug discovery, in which researchers must identify a disease-related protein's s