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Spectral decomposition of atomic structures in heterogeneous cryo-EM
We consider the problem of recovering the three-dimensional atomic structure of a flexible macromolecule from a heterogeneous cryogenic electron microscopy (cryo-EM) dataset. The dataset contains noisy tomographic projections of the electrostatic potential of the macromolecule, taken from different...
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Published in: | Inverse problems 2023-03, Vol.39 (3), p.34003 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We consider the problem of recovering the three-dimensional atomic structure of a flexible macromolecule from a heterogeneous cryogenic electron microscopy (cryo-EM) dataset. The dataset contains noisy tomographic projections of the electrostatic potential of the macromolecule, taken from different viewing directions, and in the heterogeneous case, each cryo-EM image corresponds to a different conformation of the macromolecule. Under the assumption that the macromolecule can be modelled as a chain, or discrete curve (as it is for instance the case for a protein backbone with a single chain of amino-acids), we introduce a method to estimate the deformation of the atomic model with respect to a given conformation, which is assumed to be known
a priori
. Our method consists on estimating the torsion and bond angles of the atomic model in each conformation as a linear combination of the eigenfunctions of the Laplace operator in the manifold of conformations. These eigenfunctions can be approximated by means of a well-known technique in manifold learning, based on the construction of a graph Laplacian using the cryo-EM dataset. Finally, we test our approach with synthetic datasets, for which we recover the atomic model of two-dimensional and three-dimensional flexible structures from simulated cryo-EM images. |
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ISSN: | 0266-5611 1361-6420 1361-6420 |
DOI: | 10.1088/1361-6420/acb2ba |