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Single-Particle Cryo-EM at Crystallographic Resolution
Open accessAbstract
Until only a few years ago, single-particle electron cryo-microscopy (cryo-EM) was usually not the first choice for many structural biologists due to its limited resolution in the range of nanometer to subnanometer. Now, this method rivals X-ray crystallography in terms of resolution and can be used to determine atomic structures of macromolecules that are either refractory to crystallization or difficult to crystallize in specific functional states. In this review, I discuss the recent breakthroughs in both hardware and software that transformed cryo-microscopy, enabling understanding of complex biomolecules and their functions at atomic level.
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Citations
Cites
RELION: Implementation of a Bayesian approach to cryo-EM structure determination
Scheres, S. H. W. (2012) · Journal of Structural Biology · doi:10.1016/j.jsb.2012.09.006 · Cited by 5,446
Kühlbrandt, W. (2014) · Science · doi:10.1126/science.1251652 · Cited by 1,325
Mature HIV-1 capsid structure by cryo-electron microscopy and all-atom molecular dynamics
Zhao, G., Perilla, J. R., Yufenyuy, E. L., Meng, X., Chen, B., Ning, J., Ahn, J., Gronenborn, A. M., Schulten, K., Aiken, C., et al. (2013) · Nature · doi:10.1038/nature12162 · Cited by 801
Complete subunit architecture of the proteasome regulatory particle
Lander, G. C., Estrin, E., Matyskiela, M. E., Bashore, C., Nogales, E., & Martin, A. (2012) · Nature · doi:10.1038/nature10774 · Cited by 608
Structure of the human transferrin receptor-transferrin complex
Cheng, Y., Zak, O., Aisen, P., Harrison, S. C., & Walz, T. (2004) · Cell · doi:10.1016/s0092-8674(04)00130-8 · Cited by 571
Self-citationMolecular model for a complete clathrin lattice from electron cryomicroscopy
Fotin, A., Cheng, Y., Sliz, P., Grigorieff, N., Harrison, S. C., Kirchhausen, T., & Walz, T. (2004) · Nature · doi:10.1038/nature03079 · Cited by 541
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Verba, K. A., Wang, R. Y.-R., Arakawa, A., Liu, Y., Shirouzu, M., Yokoyama, S., & Agard, D. A. (2016) · Science · doi:10.1126/science.aaf5023 · Cited by 424
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Zhang, K., Wu, H., Hoppe, N., Manglik, A., & Cheng, Y. (2022) · Nature Communications · doi:10.1038/s41467-022-32125-2 · Cited by 91
Self-citationDe novo modeling in cryo-EM density maps with Pathwalking
Chen, M., Baldwin, P. R., Ludtke, S. J., & Baker, M. L. (2016) · Journal of Structural Biology · doi:10.1016/j.jsb.2016.06.004 · Cited by 82
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Zhou, X., Li, Y., Zhang, C., Zheng, W., Zhang, G., & Zhang, Y. (2022) · Nature Computational Science · doi:10.1038/s43588-022-00232-1 · Cited by 75
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Liu, Y., Yu, Z., Lindsay, R. J., Lin, G., Chen, M., Sahoo, A., & Hanson, S. M. (2025) · PRX Life · doi:10.1103/prxlife.3.023013 · Cited by 28
Automated multiconformer model building for X-ray crystallography and cryo-EM
Wankowicz, S. A., Ravikumar, A., Sharma, S., Riley, B., Raju, A., Hogan, D. W., Flowers, J., van den Bedem, H., Keedy, D. A., & Fraser, J. S. (2024) · eLife · doi:10.7554/elife.90606 · Cited by 28
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Ho, M.-R., Wu, Y.-M., Lu, Y.-C., Ko, T.-P., & Wu, K.-P. (2023) · Journal of Structural Biology · doi:10.1016/j.jsb.2023.107958 · Cited by 8
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Metadata
- Authors
- Cheng, Y.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 161
- Issue
- 3
- Pages
- 450-457
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2039175603
- Cited by
- 581
- References
- 6
- FWCI
- 29.15
- Type
- journal article
- Language
- en
- Open access
- bronze
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