Multiscale guidance of AlphaFold3 with heterogeneous cryo-EM data
Journal:
arXiv
Published Date:
Jun 4, 2025
Abstract
Protein structure prediction models are now capable of generating accurate 3D
structural hypotheses from sequence alone. However, they routinely fail to
capture the conformational diversity of dynamic biomolecular complexes, often
requiring heuristic MSA subsampling approaches for generating alternative
states. In parallel, cryo-electron microscopy (cryo-EM) has emerged as a
powerful tool for imaging near-native structural heterogeneity, but is
challenged by arduous pipelines to go from raw experimental data to atomic
models. Here, we bridge the gap between these modalities, combining cryo-EM
density maps with the rich sequence and biophysical priors learned by protein
structure prediction models. Our method, CryoBoltz, guides the sampling
trajectory of a pretrained protein structure prediction model using both global
and local structural constraints derived from density maps, driving predictions
towards conformational states consistent with the experimental data. We
demonstrate that this flexible yet powerful inference-time approach allows us
to build atomic models into heterogeneous cryo-EM maps across a variety of
dynamic biomolecular systems including transporters and antibodies.
