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Cryo-EM reconstruction of continuous heterogeneity by Laplacian spectral volumes
被引:33
|作者:
Moscovich, Amit
[1
]
Halevi, Amit
[1
]
Anden, Joakim
[2
]
Singer, Amit
[1
,3
]
机构:
[1] Princeton Univ, Program Appl & Computat Math, Princeton, NJ 08544 USA
[2] Flatiron Inst, Ctr Computat Math, New York, NY USA
[3] Princeton Univ, Dept Math, Princeton, NJ 08544 USA
关键词:
single particle electron cryomicroscopy;
heterogeneity;
tomographic reconstruction;
molecular conformation space;
manifold learning;
Laplacian eigenmaps;
diffusion maps;
FOURIER;
CLASSIFICATION;
VARIANCE;
MACROMOLECULES;
VARIABILITY;
PROJECTIONS;
COVARIANCE;
D O I:
10.1088/1361-6420/ab4f55
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
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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页数:31
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