Heterogeneous reconstruction of deformable atomic models in Cryo-EM
This work addresses the problem of structural heterogeneity for researchers in structural biology, but it is incremental as it builds on existing physics-based methods and focuses on synthetic data.
The authors tackled the challenge of explaining structural heterogeneity in biomolecules with atomic models in cryo-EM by developing a method based on normal mode analysis and an autoencoder, achieving atomic-level accuracy in recapitulating intermediate atomic models on synthetic datasets.
Cryogenic electron microscopy (cryo-EM) provides a unique opportunity to study the structural heterogeneity of biomolecules. Being able to explain this heterogeneity with atomic models would help our understanding of their functional mechanisms but the size and ruggedness of the structural space (the space of atomic 3D cartesian coordinates) presents an immense challenge. Here, we describe a heterogeneous reconstruction method based on an atomistic representation whose deformation is reduced to a handful of collective motions through normal mode analysis. Our implementation uses an autoencoder. The encoder jointly estimates the amplitude of motion along the normal modes and the 2D shift between the center of the image and the center of the molecule . The physics-based decoder aggregates a representation of the heterogeneity readily interpretable at the atomic level. We illustrate our method on 3 synthetic datasets corresponding to different distributions along a simulated trajectory of adenylate kinase transitioning from its open to its closed structures. We show for each distribution that our approach is able to recapitulate the intermediate atomic models with atomic-level accuracy.