esearchers at Google DeepMind have developed AlphaFold 3, an AI model that can predict the structure of and interactions between biological molecules including proteins, DNA and RNA, and small molecules that could function as drugs. Google DeepMind will make the model available for non-commercial use through“It's a big milestone for us today, announcing AlphaFold 3,” said Demis Hassabis, CEO of Google DeepMind, at a briefing on May 7 announcing the breakthrough.
AlphaFold 3 goes further by predicting the structures of almost all biological molecules and modeling the interactions between those molecules. While researchers have long developed specialized computational methods for modeling interactions between specific types of biological molecules, AlphaFold 3 marks the first time that a single system has been able to predict the interactions between nearly all molecular types with state-of-the-art performance.
The properties and functions of molecules in biological systems are typically a result of how they interact with other molecules. Using experiments to understand molecular interactions can take years of research time and be prohibitively expensive. If these interactions can instead be estimated computationally with sufficient accuracy, then biological research can be dramatically accelerated.
“AlphaFold continues to get better, and increasingly more relevant for biological investigations,” said Paul Nurse, the Nobel Prize-winning geneticist and chief executive and director of the London-based biomedical research center the Francis Crick Institute, in a statement accompanying the Google DeepMind announcement.
“We've been using AlphaFold 3’s capabilities day-to-day in our drug design programmes,” said Max Jaderberg, chief AI officer at Isomorphic labs, at the announcement briefing. “We're already seeing that potential to accelerate, improve, and ultimately transform the way that we do drug discovery, and it's really because of the new level of accuracy of this model, and the increased breadth of biomolecules that this model is able to predict, that really enables that for us.