期刊
JOURNAL OF STRUCTURAL BIOLOGY
卷 214, 期 4, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jsb.2022.107915
关键词
Electron microscopy; Single Particle Analysis; Validation
资金
- Ministerio de Ciencia, Innovacion y Universidades, Agencia Estatal de Investigaci?on [PID2019-109820RB-I00, MCIN/AEI/10.13039/501100011033]
- European Regional Development Fund (ERDF)
- MICIN
- European Strategic Infrastructure Project (ESFRI) in the area of Structural Biology [PID2019-104757RB-I00, MCIN/AEI/10.13039/501100011033/and ?]
- ERDF A way of making Europe
- European Union
- Comunidad Autonoma de Madrid [S2017/BMD-3817]
- Instituto de Salud Carlos III [IMP/00019]
- European Union, European Regional Development Fund (ERDF)
- CSIC
- JAE Intro Program [JAEINT_20_01330]
- European Union (EU) [810057]
- European Research Council (ERC) [810057] Funding Source: European Research Council (ERC)
Single-Particle Analysis by Cryo-Electron Microscopy is a technique used to determine the 3D structure of biological macromolecules. This article introduces HaPi, a method that automatically determines the handedness of macromolecule electron density maps solved by CryoEM. HaPi utilizes convolutional neural networks and a consensus strategy to determine the hand of the maps.
Single-Particle Analysis by Cryo-Electron Microscopy is a well-established technique to elucidate the three-dimensional (3D) structure of biological macromolecules. The orientation of the acquired projection images must be initially estimated without any reference to the final structure. In this step, algorithms may find a mirrored version of all the orientations resulting in a mirrored 3D map. It is as compatible with the acquired images as its unmirrored version from the image processing point of view, only that it is not biologically plausible. In this article, we introduce HaPi (Handedness Pipeline), the first method to automatically determine the hand of electron density maps of macromolecules solved by CryoEM. HaPi is built by training two 3D convolutional neural networks. The first determines alpha-helices in a map, and the second determines whether the alpha-helix is left-handed or right-handed. A consensus strategy defines the overall map hand. The pipeline is trained on simulated and experimental data. The handedness can be detected only for maps whose resolution is better than 5 angstrom. HaPi can identify the hand in 89% of new simulated maps correctly. Moreover, we evaluated all the maps deposited at the Electron Microscopy Data Bank and 11 structures uploaded with the incorrect hand were identified.
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