Cargando…
Mapping the motion and structure of flexible proteins from cryo-EM data
A deep learning algorithm maps out the continuous conformational changes of flexible protein molecules from single-particle cryo-electron microscopy images, allowing the visualization of the conformational landscape of a protein with improved resolution of its moving parts.
Formato: | Online Artículo Texto |
---|---|
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10174731/ https://www.ncbi.nlm.nih.gov/pubmed/37169930 http://dx.doi.org/10.1038/s41592-023-01883-2 |
Ejemplares similares
-
3DFlex: determining structure and motion of flexible proteins from cryo-EM
por: Punjani, Ali, et al.
Publicado: (2023) -
Multi-Scale Flexible Fitting of Proteins to Cryo-EM Density Maps at Medium Resolution
por: Kulik, Marta, et al.
Publicado: (2021) -
Methods to account for movement and flexibility in cryo-EM data processing
por: Rawson, S., et al.
Publicado: (2016) -
Interpreting the cryo-EM map
por: Rosenthal, Peter B.
Publicado: (2019) -
Namdinator – automatic molecular dynamics flexible fitting of structural models into cryo-EM and crystallography experimental maps
por: Kidmose, Rune Thomas, et al.
Publicado: (2019)