Geometric shape matching for recovering protein conformations from single-particle Cryo-EM data
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913171126616064 |
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| author | Jansson, Erik Krook, Jonathan Modin, Klas Öktem, Ozan |
| author_facet | Jansson, Erik Krook, Jonathan Modin, Klas Öktem, Ozan |
| contents | We address recovery of the three-dimensional backbone structure of single polypeptide proteins from single-particle cryo-electron microscopy (Cryo-SPA) data. Cryo-SPA produces noisy tomographic projections of electrostatic potentials of macromolecules. From these projections, we use methods from shape analysis to recover the three-dimensional backbone structure. Thus, we view the reconstruction problem as an indirect matching problem, where a point cloud representation of the protein backbone is deformed to match 2D tomography data. The deformations are obtained via the action of a matrix Lie group. By selecting a deformation energy, the optimality conditions are obtained, which lead to computational algorithms for optimal deformations. We showcase our approach on synthetic data, for which we recover the three-dimensional structure of the backbone. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_00833 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Geometric shape matching for recovering protein conformations from single-particle Cryo-EM data Jansson, Erik Krook, Jonathan Modin, Klas Öktem, Ozan Biomolecules Numerical Analysis Differential Geometry Optimization and Control 53Z50, 90C26, 68U10, 53Z10, 92C55 We address recovery of the three-dimensional backbone structure of single polypeptide proteins from single-particle cryo-electron microscopy (Cryo-SPA) data. Cryo-SPA produces noisy tomographic projections of electrostatic potentials of macromolecules. From these projections, we use methods from shape analysis to recover the three-dimensional backbone structure. Thus, we view the reconstruction problem as an indirect matching problem, where a point cloud representation of the protein backbone is deformed to match 2D tomography data. The deformations are obtained via the action of a matrix Lie group. By selecting a deformation energy, the optimality conditions are obtained, which lead to computational algorithms for optimal deformations. We showcase our approach on synthetic data, for which we recover the three-dimensional structure of the backbone. |
| title | Geometric shape matching for recovering protein conformations from single-particle Cryo-EM data |
| topic | Biomolecules Numerical Analysis Differential Geometry Optimization and Control 53Z50, 90C26, 68U10, 53Z10, 92C55 |
| url | https://arxiv.org/abs/2410.00833 |