Learning residue level protein dynamics with multiscale Gaussians

ArXi:2509.01038v2 Announce Type: replace-cross Many methods have been developed to predict static protein structures,. however. understanding the dynamics of protein structure is essential for elucidating biological function. While molecular dynamics (MD) simulations remain the in silico gold standard, its high computational cost limits scalability. We present DynaProt, a lightweight, SE(3)-invariant framework that predicts rich descriptors of protein dynamics directly from static structures.