EMPIAR-13496 - Cryo-EM of SARS-CoV-2 frame shift stimulation element [multiple data sets in MRC format]

EMPIAR-13496

Cryo-EM of SARS-CoV-2 frame shift stimulation element [multiple data sets in MRC format]

Publication:

Cryo-EM and antisense targeting of the 28-kDa frameshift stimulation element from the SARS-CoV-2 RNA genome

Zhang K, Zheludev IN, Hagey RJ, Haslecker R, Hou YJ, Kretsch R, Pintilie GD, Rangan R, Kladwang W, Li S, Wu MT, Pham EA, Bernardin-Souibgui C, Baric RS, Sheahan TP, D'Souza V, Glenn JS, Chiu W, Das R

Nature structural & molecular biology 28 (2021) 747-754

PMID: 34426697

DOI: 10.1038/s41594-021-00653-y

Related EMDB entry:

EMD-22296 EMD-22297

Deposited:

2026-01-06

Released:

2026-04-28

Last modified:

2026-04-28

Imageset size:

13.73 TB

Imageset DOI:

10.6019/EMPIAR-13496

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned multiframe micrographs of SARS-CoV-2 Frameshift Stimulation Element

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

10010

Image size:

(None, None)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.82, 0.82)

Details:

The final datasets in this study were imaged in a Titan Krios cryo-electron microscope (Thermo Fisher Scientific) operated at 300 kV with a GIF energy filter (Gatan) at a magnification of ×165,000 (corresponding to a calibrated sampling of 0.82 Å per pixel) for both samples. Micrographs were recorded by EPU software (Thermo Fisher Scientific) with a Gatan K2 Summit direct electron detector, where each image was composed of 30 individual frames with an exposure time of 6 s and an exposure rate of 8.3 electrons per second per Å2.

Files:

This entry cannot be downloaded from PDBj.

Archives and downloads the selected files into an uncompressed zip file.

Depending on the number and size of files to be downloaded, this can take an enormous amount of time. Also, this feature is unstable and may not work properly, and checksums of downloaded files are not verified.

We recommend using rsync, aspera, globus, etc.

Download a list of selected files.

It is possible to download files by specifying the file list with rsync command, etc.

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

2. Unaligned multiframe micrographs of SARS-CoV-2 Frameshift Stimulation Element

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

13155

Image size:

(None, None)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.82, 0.82)

Details:

Files:

This entry cannot be downloaded from PDBj.

Archives and downloads the selected files into an uncompressed zip file.

We recommend using rsync, aspera, globus, etc.

Download a list of selected files.

It is possible to download files by specifying the file list with rsync command, etc.

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

3. Unaligned multiframe micrographs of SARS-CoV-2 Frameshift Stimulation Element Tagged with ATP-TTR3 nanostructure

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

2714

Image size:

(None, None)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.82, 0.82)

Details:

Files:

This entry cannot be downloaded from PDBj.

Archives and downloads the selected files into an uncompressed zip file.

We recommend using rsync, aspera, globus, etc.

Download a list of selected files.

It is possible to download files by specifying the file list with rsync command, etc.

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

4. Unaligned multiframe micrographs of SARS-CoV-2 Frameshift Stimulation Element Tagged with ATP-TTR3 nanostructure

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

9455

Image size:

(None, None)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.82, 0.82)

Details:

Files:

This entry cannot be downloaded from PDBj.

Archives and downloads the selected files into an uncompressed zip file.

We recommend using rsync, aspera, globus, etc.

Download a list of selected files.

It is possible to download files by specifying the file list with rsync command, etc.

rsync -av --files-from=(path-to-filelist) rsync://empiar.pdbj.org/empiar/archive (path-to-destination)

Browse All Files

Quick Links

Browse EMPIAR

Sample Preparation Widget

Volume Browser

Tomo Viewer Prototype

Claim entries to your ORCiD

Talks and Tutorials

EMPIAR Quick tour

Publications

Re-use study

Statistics

EMPIAR in the news

COVID-19 Data Portal

EMDB

BioImage Archive

PDBe

EMNavigator@PDBj

PDBj

Citations

prismPYP: Power-spectrum and image domain learning for self-supervised micrograph evaluation.

He L, Bartesaghi A. (2026)

CryoSIP: unleashing protein high-resolution Cryo-EM via semantic-instance collaborative picking.

Deng Y, Wang S, Xiang M, Li Y, Zhuo L, Cao D, Fu X, Zou Q. (2026)

Chart builder: an interactive tool for user driven data visualization in the electron microscopy data bank.

Fonseca N, Duraisamy AK, Wang Z, Somasundharam S, Tayebinia M, de Oliveira LC, Ma M, Turner J, Patwardhan A, Kleywegt GJ, Hartley M, Morris KL. (2026)

CryoVirusDB: An Annotated Dataset for AI-Based Virus Particle Identification in Cryo-EM Micrographs.

Gyawali R, Dhakal A, Wang L, Cheng J. (2026)

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements.

Jones HN, Deshmukh A, Pande K. (2026)

CryoGS: High-Quality Cryo-EM Homogeneous Reconstruction by Gaussian Splatting

Zeng B, Liu S, Cheng S, Xu G, Fan H. (2026)

Point cloud deformation modeling for particle selection following cryo-EM 2D classification.

Wang X, Mo Z, Li F, Zhang F, Wan X. (2026)

ICECREAM: high-fidelity equivariant cryo-electron tomography.

Kishore V, Debarnot V, Righetto RD, Engel BD, Dokmanić I. (2026)

CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection.

Schäfer JH, Calza A, Hom K, Damodar P, Peng R, Bogdanović N, Lander GC, Stagg SM, Cianfrocco MA. (2025)