EMPIAR-11178 - Human NTCP in complex with YN69083 Fab [multiple data sets in TIFF format]

EMPIAR-11178

Human NTCP in complex with YN69083 Fab [multiple data sets in TIFF format]

Publication:

Structural insights into the HBV receptor and bile acid transporter NTCP

Park JH, Iwamoto M, Yun JH, Uchikubo-Kamo T, Son D, Jin Z, Yoshida H, Ohki M, Ishimoto N, Mizutani K, Oshima M, Muramatsu M, Wakita T, Shirouzu M, Liu K, Uemura T, Nomura N, Iwata S, Watashi K, Tame JRH, Nishizawa T, Lee W, Park SY

Nature 606 (2022) 1027-1031

PMID: 35580630

DOI: 10.1038/s41586-022-04857-0

Related EMDB entry:

EMD-31526

Deposited:

2022-08-18

Released:

2022-09-09

Last modified:

2022-09-09

Imageset size:

5.49 TB

Imageset DOI:

10.6019/EMPIAR-11178

Experimental metadata:

Download xml json

Deposited via PDBj

Contains:

micrographs - multiframe

Image Sets

1. Unaligned, non-dose weighted movies of NTCP-YN69083Fab Data 1

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

5845

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.829, 0.829)

Details:

HT: 300 kV
Cs: 2.7 mm
Flux: 50 e/Å2 in 49 frames

'FoilHole_18713532_Data_18692370_18692372_20210120_003013_GainReference.tiff' is a super-resolution gain reference written by EPU.
You have to downscale it by 2 with harmonic mean. This can be done with EMAN2 as:
e2proc2d.py --process math.reciprocal --meanshrink 2 --process
math.reciprocal FoilHole_18713532_Data_18692370_18692372_20210120_003013_GainReference.tiff dataset1-gain.mrc
The gain does not need any rotation or flipping.

The dataset was collected with AFIS. AFIS directions are available in XMLs files, although grouping was not applied during processing.
Unfortunately, an XML file for FoilHole_18729909_Data_18692370_18692372_20210120_104541_Fractions.tiff was lost.

NB: The pixel size in the TIFF header is not correct.
Although the paper says 5846 movies, one of them was corrupted, so only 5845 were used for processing.

Files:

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We recommend using rsync, aspera, globus, etc.

Download a list of selected files.

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

2. Unaligned, non-dose weighted movies of NTCP-YN69083Fab Data 2

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

15121

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.829, 0.829)

Details:

HT: 300 kV
Cs: 2.7 mm
Flux: 64 e/Å2 in 65 frames

'FoilHole_18796351_Data_18756374_18756376_20210220_200533_gain.tiff' is a super-resolution gain reference written by EPU.
You have to downscale it by 2 with harmonic mean. This can be done with EMAN2 as:
e2proc2d.py --process math.reciprocal --meanshrink 2 --process
math.reciprocal FoilHole_18796351_Data_18756374_18756376_20210220_200533_gain.tiff dataset2-gain.mrc
The gain does not need any rotation or flipping.

Please exclude the first frame from motion correction and Polishing, because it is corrupted due to glitches in the K3 CDS mode.
The dataset was collected with AFIS. AFIS directions are available in XMLs files, although grouping was not applied during processing.
Unfortunately, XML files for FoilHole_18775720_Data_18756374_18756376_20210220_023647_fractions.tiff and FoilHole_18816258_Data_18756374_18756376_20210221_102409_fractions.tiff were lost.

NB: The pixel size in the TIFF header is not correct.

Files:

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

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Hicks CW, Rahman S, Gloor SL, Fields JK, Husby NL, Vaidya A, Maier KE, Morgan M, Keogh MC, Wolberger C. (2024)

Molecular recognition of an odorant by the murine trace amine-associated receptor TAAR7f.

Gusach A, Lee Y, Khoshgrudi AN, Mukhaleva E, Ma N, Koers EJ, Chen Q, Edwards PC, Huang F, Kim J, Mancia F, Veprintsev DB, Vaidehi N, Weyand SN, Tate CG. (2024)

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Kofler L, Grundmann L, Gerhalter M, Prattes M, Merl-Pham J, Zisser G, Grishkovskaya I, Hodirnau VV, Vareka M, Breinbauer R, Hauck SM, Haselbach D, Bergler H. (2024)

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