  The 2.5-MDa 26S proteasome maintains proteostasis and regulates myriad
cellular processes. How polyubiquitylated substrate interactions regulate
proteasome activity is not understood. Here we introduce a deep manifold
learning framework, named AlphaCryo4D, which enables atomic-level cryogenic
electron microscopy (cryo-EM) reconstructions of nonequilibrium conformational
continuum and reconstitutes hidden dynamics of proteasome autoregulation in the
act of substrate degradation. AlphaCryo4D integrates 3D deep residual learning
with manifold embedding of free-energy landscapes, which directs 3D clustering
via an energy-based particle-voting algorithm. In blind assessments using
simulated heterogeneous cryo-EM datasets, AlphaCryo4D achieved 3D
classification accuracy three times that of conventional method and
reconstructed continuous conformational changes of a 130-kDa protein at
sub-3-angstrom resolution. By using AlphaCryo4D to analyze a single
experimental cryo-EM dataset, we identified 64 conformers of the
substrate-bound human 26S proteasome, revealing conformational entanglement of
two regulatory particles in the doubly capped holoenzymes and their energetic
differences with singly capped ones. Novel ubiquitin-binding sites are
discovered on the RPN2, RPN10 and Alpha5 subunits to remodel polyubiquitin
chains for deubiquitylation and recycle. Importantly, AlphaCryo4D choreographs
single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during
translocation initiation, which upregulates proteolytic activity by
allosterically promoting nucleophilic attack. Our systemic analysis illuminates
a grand hierarchical allostery for proteasome autoregulation.
