BioEmu-1 is a deep learning model that can generate thousands of protein structures per hour on a single graphics processing unit. It provides orders of magnitude greater computational efficiency compared to classical MD simulations, thereby opening the door to insights that have, until now, been out of reach.

From forming muscle fibers to protecting us from disease, proteins play an essential role in almost all biological processes in humans and other life forms alike. There has been extraordinary progress in recent years toward better understanding protein structures using deep learning, enabling the accurate prediction of protein structures from their amino acid sequences. However, predicting a single protein structure from its amino acid sequence is like looking at a single frame of a movie—it offers only a snapshot of a highly flexible molecule. Biomolecular Emulator-1 (BioEmu-1) is a deep-learning model that provides scientists with a glimpse into the rich world of different structures each protein can adopt, or structural ensembles, bringing us a step closer to understanding how proteins work. A deeper understanding of proteins enables us to design more effective drugs, as many medications work by influencing protein structures to boost their function or prevent them from causing harm.