Journal
INVERSE PROBLEMS
Volume 36, Issue 2, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1361-6420/ab4f55
Keywords
single particle electron cryomicroscopy; heterogeneity; tomographic reconstruction; molecular conformation space; manifold learning; Laplacian eigenmaps; diffusion maps
Categories
Funding
- NIGMS [R01GM090200]
- AFOSR [FA9550-17-1-0291]
- ARO [W911NF-17-1-0512]
- Simons Investigator Award
- Moore Foundation Data-Driven Discovery Investigator Award
- NSF BIGDATA Award [IIS-1837992]
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Single-particle electron cryomicroscopy is an essential tool for high-resolution 3D reconstruction of proteins and other biological macromolecules. An important challenge in cryo-EM is the reconstruction of non-rigid molecules with parts that move and deform. Traditional reconstruction methods fail in these cases, resulting in smeared reconstructions of the moving parts. This poses a major obstacle for structural biologists, who need high-resolution reconstructions of entire macromolecules, moving parts included. To address this challenge, we present a new method for the reconstruction of macromolecules exhibiting continuous heterogeneity. The proposed method uses projection images from multiple viewing directions to construct a graph Laplacian through which the manifold of three-dimensional conformations is analyzed. The 3D molecular structures are then expanded in a basis of Laplacian eigenvectors, using a novel generalized tomographic reconstruction algorithm to compute the expansion coefficients. These coefficients, which we name spectral volumes, provide a high-resolution visualization of the molecular dynamics. We provide a theoretical analysis and evaluate the method empirically on several simulated data sets.
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