EMPIAR-12772 - Progesterone-bound DB3 Fab in complex with computationally designed DBPro1156_2 protein binder [multiple data sets in MRC format]

EMPIAR-12772

Progesterone-bound DB3 Fab in complex with computationally designed DBPro1156_2 protein binder [multiple data sets in MRC format]

Publication:

Targeting protein-ligand neosurfaces with a generalizable deep learning tool

Marchand A, Buckley S, Schneuing A, Pacesa M, Elia M, Gainza P, Elizarova E, Neeser RM, Lee PW, Reymond L, Miao Y, Scheller L, Georgeon S, Schmidt J, Schwaller P, Maerkl SJ, Bronstein M, Correia BE

Nature (2025)

PMID: 39814890

DOI: 10.1038/s41586-024-08435-4

Related EMDB entry:

EMD-50522

Deposited:

2025-02-11

Released:

2025-10-29

Last modified:

2025-10-29

Imageset size:

14.63 TB

Imageset DOI:

10.6019/EMPIAR-12772

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe
micrographs - single frame

Image Sets

1. Unaligned multi-frame movies of Progesterone-bound DB3 Fab in complex with computationally designed DBPro1156_2 protein binder

Category:

micrographs - multiframe

Image format:

MRC

No. of images or tilt series:

34507

Image size:

(4096, 4096)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.658, 0.658)

Details:

---

Files:

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2. Aligned dose-weighted micrographs of Progesterone-bound DB3 Fab in complex with computationally designed DBPro1156_2 protein binder

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

34507

Image size:

(4096, 4096)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.658, 0.658)

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)

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Citations

AlignPCA-2D: PCA-reduced Euclidean vector alignment for 2D classification in cryo-EM.

Ramírez-Aportela E, Zarrabeitia OL, Fonseca YC, Ceska T, Subramaniam S, Carazo JM, Sorzano COS. (2026)

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)

Helical reconstruction of amyloids in cryoSPARC.

Schaefer JH, O'Neill RT, Donnelly JP, Powers ET, Kelly JW, Lander GC. (2026)

An unattended image-processing pipeline for on-the-fly quality assessment and 3D exploration in cryo-EM.

Marchán Torres D, Conesa P, Garcia A, Iceta M, Broche L, Gragera M, Linares R, Kwong HS, Chichón FJ, Svensson O, Arranz R, Effantin G, Kandiah E, Carazo JM, Sorzano COS. (2026)

CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.

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.

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

Unbend, correction of local beam-induced sample motion in cryo-EM images using a 3D spline model.

Kong L, Zottig X, Elferich J, Grigorieff N. (2026)

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

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

CryoWriter: a robotic solution for improved Cryo-EM grid preparation.

Kv C, Ekundayo B, Di Fabrizio M, Mohammed I, Radecke J, Stahlberg H, Kube M. (2026)