Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics

ArXi:2604.25244v1 Announce Type: cross Protein dynamics underlie many biological functions, yet remain difficult to characterize due to the high computational cost of molecular dynamics simulations and the scarcity of dynamic structural data. This survey reviews recent advances in artificial intelligence for protein dynamics from three perspectives: learning from structural ensembles and trajectories, learning from physical energy signals, and learning to accelerate molecular simulations.