Protein structures and artificial intelligence join forces to transform drug combination therapy
Peer-Reviewed Publication
Updates every hour. Last Updated: 21-Aug-2025 04:10 ET (21-Aug-2025 08:10 GMT/UTC)
A team of international researchers has published a comprehensive review in Advanced Science detailing how combining protein three-dimensional spatial structures with artificial intelligence is reshaping the way scientists predict and design drug combinations. By integrating high-resolution protein modeling with advanced AI algorithms, the approach offers unprecedented accuracy in identifying synergistic and antagonistic effects, paving the way for safer and more effective treatments for cancer, infectious diseases, and metabolic disorders.
Professor Seungbum Koo’s research team received the Clinical Biomechanics Award at the 30th International Society of Biomechanics (ISB) Conference, held in July 2025 in Stockholm, Sweden. The Plenary Lecture was delivered by first author and Ph.D. candidate Jeongseok Oh. This research was conducted in collaboration with Professor Joon-Ho Wang’s team at Samsung Medical Center.
Folding structures are widely used in robot design as an intuitive and efficient shape-morphing mechanism, with applications explored in space and aerospace robots, soft robots, and foldable grippers (hands). However, existing folding mechanisms have fixed hinges and folding directions, requiring redesign and reconstruction every time the environment or task changes. A Korean research team has now developed a “field-programmable robotic folding sheet” that can be programmed in real time according to its surroundings, significantly enhancing robots’ shape-morphing capabilities and opening new possibilities in robotics.
KAIST (President Kwang Hyung Lee) announced on the 6th that Professors Jung Kim and Inkyu Park of the Department of Mechanical Engineering have developed the foundational technology for a “field-programmable robotic folding sheet” that enables real-time shape programming.
A research team has shed light on how water lilies produce their vibrant petal colors, revealing key genes involved in blue, red, and white coloration.
A research team has uncovered the unexpected role of the cassava ferritin-like gene MeFER4 in plant stress responses.