EMPOT: partial alignment of density maps and rigid body fitting using unbalanced Gromov-Wasserstein divergence
arXiv (Cornell University)(2023)
摘要
Aligning EM density maps and fitting atomic models are essential steps in
single particle cryogenic electron microscopy (cryo-EM), with recent methods
leveraging various algorithms and machine learning tools. As aligning maps
remains challenging in the presence of a map that only partially fits the other
(e.g. one subunit), we here propose a new procedure, EMPOT (EM Partial
alignment with Optimal Transport), for partial alignment of 3D maps. EMPOT
first finds a coupling between 3D point-cloud representations, which is
associated with their so-called unbalanced Gromov Wasserstein divergence, and
second, uses this coupling to find an optimal rigid body transformation. Upon
running and benchmarking our method with experimental maps and structures, we
show that EMPOT outperforms standard methods for aligning subunits of a protein
complex and fitting atomic models to a density map, suggesting potential
applications of Partial Optimal Transport for improving Cryo-EM pipelines.
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关键词
density maps,partial alignment,rigid body,gromov-wasserstein
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