EMPIAR-13591 - Cryo-EM structure of rat SLCO2A1 bound to losartan. [26341 multi-frame micrographs composed of 40 frames each in TIFF format]

EMPIAR-13591

Cryo-EM structure of rat SLCO2A1 bound to losartan. [26341 multi-frame micrographs composed of 40 frames each in TIFF format]

Publication:

Structural basis for prostaglandin and drug transport via SLCO2A1

Joshi C, Deme JC, Nakamura Y, Hsu WT, Goult JD, Kato T, Parker JL, Biggin PC, Lea SM, Nakanishi T, Newstead S

Nature communications 17 (2026)

PMID: 41862483

DOI: 10.1038/s41467-026-70227-3

Related EMDB entry:

EMD-53483

Deposited:

2026-05-19

Released:

2026-06-23

Last modified:

2026-06-23

Imageset size:

4.96 TB

Imageset DOI:

10.6019/EMPIAR-13591

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Raw and unaligned multi frame movies for rat SLCO2A1 bound to losartan.

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

26341

Image size:

(None, None)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(None, None)

Details:

The micrographs are the raw movie frames (4092x5760) collected on a 300kV Titan Krios microscope. The datasets are organised into 3 sets with following parameters:
Set I: 8575 movies, Total dose 40.2 e/Å^2, Pixel size 0.832Å, TIFF format. No tilt series.
Set II: 4106 movies, Total dose 49.2 e/Å^2, Pixel size 0.832Å, TIFF format. No tilt series.
Set III: 13,660 movies, Total dose 46.22 e/Å^2 , Pixel size 0.832Å, TIFF format. No tilt series.

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Citations

A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.

Yu C, Xu Z, Zeng Q, Wan X, El-Messiry H, Zhang F, Han R. (2026)

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Poudel B, Gyawali R, Dhakal A, Cheng J, Xu D. (2026)

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.

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

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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)

See all citations

Protein Data Bank Japan News

[2026-06-24]

379件のPDBエントリーが新たに公開されました。（2026-06-24付）