EMPIAR-11858 - β2-adrenergic receptor in complex with GTP-bound G protein Gs, vitrified 17 seconds after addition of GTP [12930 multi-frame micrographs composed of 79 frames each in TIFF format]

EMPIAR-11858

β2-adrenergic receptor in complex with GTP-bound G protein Gs, vitrified 17 seconds after addition of GTP [12930 multi-frame micrographs composed of 79 frames each in TIFF format]

Publication:

Time-resolved cryo-EM of G-protein activation by a GPCR

Papasergi-Scott MM, Pérez-Hernández G, Batebi H, Gao Y, Eskici G, Seven AB, Panova O, Hilger D, Casiraghi M, He F, Maul L, Gmeiner P, Kobilka BK, Hildebrand PW, Skiniotis G

Nature (2024)

PMID: 38480881

DOI: 10.1038/s41586-024-07153-1

Related EMDB entry:

EMD-40146 EMD-40141 EMD-40143 EMD-40151 EMD-40142 EMD-40153 EMD-40136 EMD-40139 EMD-40140 EMD-29986

Deposited:

2024-01-20

Released:

2024-06-18

Last modified:

2024-06-18

Imageset size:

7.98 TB

Imageset DOI:

10.6019/EMPIAR-11858

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned multi-frame micrographs of β2-adrenergic receptor in complex with GTP-bound G protein Gs, vitrified 17 seconds after GTP addition

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

12930

Image size:

(11520, 8184)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.43385, 0.43385)

Details:

Raw unaligned movie files (tif format, 79 frames, not gain corrected), and gain correction image (mrc format).
Cryo-EM imaging of the β2AR-Gs(GTP) complex was performed on a Titan Krios electron microscope operated at 300 kV accelerating voltage, and equipped with a K3 Summit direct electron detector and post column energy filter. Super-resolution pixel size: 0.43385Å. Μovies were obtained at an exposure rate of 32.46 electrons/Å^2/sec. The total exposure time was 1.999 sec over 79 frames per movie stack.

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Citations

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Kim K, Li H, Clarke OB. (2025)

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PERC: a suite of software tools for the curation of cryoEM data with application to simulation, modeling and machine learning.

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Overcoming Preferred Orientation in Cryo-EM With Ultrasonic Excitation During Vitrification

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