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- EMDB-75648: Struct2SeQ designed RNA molecule -

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Basic information

Entry
Database: EMDB / ID: EMD-75648
TitleStruct2SeQ designed RNA molecule
Map datafull map
Sample
  • Complex: De novo design of RNA Kissing Multiloops using Struct2SeQ
    • RNA: RNA
Keywordssynthetic / pseudoknot / kissing multiloops / RNA
Biological speciesEscherichia phage T7 (virus) / synthetic construct (others)
Methodsingle particle reconstruction / cryo EM / Resolution: 4.7 Å
AuthorsMancino A / Hingey J / He S / Haack DB / Rudolfs B / Spellmon N / Yu Z / Toor N / Das R
Funding support United States, 1 items
OrganizationGrant numberCountry
Howard Hughes Medical Institute (HHMI) United States
CitationJournal: Science / Year: 2026
Title: De novo design of RNA pseudoknots with deep learning.
Authors: Jill Townley / Wipapat Kladwang / David Baker / Hamish M Blair / Christian A Choe / Gina El Nesr / Andrew Favor / Eli Fisker / Daniel B Haack / Shujun He / Jason Hingey / Po-Ssu Huang / Rui ...Authors: Jill Townley / Wipapat Kladwang / David Baker / Hamish M Blair / Christian A Choe / Gina El Nesr / Andrew Favor / Eli Fisker / Daniel B Haack / Shujun He / Jason Hingey / Po-Ssu Huang / Rui Huang / Chaitanya K Joshi / Thomas Karagianes / Andrew Kubaney / Pietro Liò / Adamo Mancino / Jonathan Romano / Boris Rudolfs / Nicholas Spellmon / Navtej Toor / Jigyasa Verma / Vivian Wu / Zhiheng Yu / Eterna Participants / Rhiju Das /
Abstract: RNA design has been hindered by the limited accuracy of three-dimensional (3D) structure prediction. In this study, we show that intricate RNA structures can be generated with current deep learning ...RNA design has been hindered by the limited accuracy of three-dimensional (3D) structure prediction. In this study, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an Eterna competition involving 57 pseudoknots, generative artificial intelligence (AI) methods matched experienced human designers in solving most blind challenges, evaluated by single nucleotide-resolution chemical mapping, compensatory mutagenesis, and cryo-electron microscopy. AI-generated molecules with accurate secondary structures formed well-ordered 3D folds stabilized by noncanonical tertiary interactions not modeled during design. Success was guided by an RNet foundation model trained on prior chemical mapping data, suggesting that some difficult RNA design tasks may be tractable without first solving RNA 3D structure prediction.
History
DepositionFeb 18, 2026-
Header (metadata) releaseMay 27, 2026-
Map releaseMay 27, 2026-
UpdateSep 9, 2026-
Current statusSep 9, 2026Processing site: RCSB / Status: Released

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Structure visualization

Supplemental images

emd_75648.png

Downloads & links

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Map

FileDownload / File: emd_75648.map.gz / Format: CCP4 / Size: 52.7 MB / Type: IMAGE STORED AS FLOATING POINT NUMBER (4 BYTES)
Annotationfull map
Projections & slices

Image control

Size
Brightness
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AxesZ (Sec.)Y (Row.)X (Col.)
1.47 Å/pix.
x 240 pix.
= 352.128 Å		1.47 Å/pix.
x 240 pix.
= 352.128 Å		1.47 Å/pix.
x 240 pix.
= 352.128 Å

Surface

Projections

Slices (1/3)

Slices (1/2)

Slices (2/3)

Images are generated by Spider.

Voxel sizeX=Y=Z: 1.4672 Å
Density

Histogram

Histogram (log scale)
Contour LevelBy AUTHOR: 0.03
Minimum - Maximum-4.7707033 - 8.273987
Average (Standard dev.)0.0001631078 (±0.07745069)
SymmetrySpace group: 1
Details

EMDB XML:

Map geometry
Axis orderXYZ
Origin000
Dimensions240240240
Spacing240240240
CellA=B=C: 352.128 Å
α=β=γ: 90.0 °

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Supplemental data

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Additional map: full map

Fileemd_75648_additional_1.map
Annotationfull map
Projections & Slices
AxesZYX

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Slices (1/2)
Density Histograms

Histogram

Histogram (log scale)

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Half map: full map

Fileemd_75648_half_map_1.map
Annotationfull map
Projections & Slices
AxesZYX

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Slices (1/2)
Density Histograms

Histogram

Histogram (log scale)

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Half map: full map

Fileemd_75648_half_map_2.map
Annotationfull map
Projections & Slices
AxesZYX

Projections

Slices (1/2)
Density Histograms

Histogram

Histogram (log scale)

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Sample components

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Entire : De novo design of RNA Kissing Multiloops using Struct2SeQ

EntireName: De novo design of RNA Kissing Multiloops using Struct2SeQ
Components
  • Complex: De novo design of RNA Kissing Multiloops using Struct2SeQ
    • RNA: RNA

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Supramolecule #1: De novo design of RNA Kissing Multiloops using Struct2SeQ

SupramoleculeName: De novo design of RNA Kissing Multiloops using Struct2SeQ
type: complex / ID: 1 / Parent: 0 / Macromolecule list: all
Source (natural)Organism: Escherichia phage T7 (virus)

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Macromolecule #1: RNA

MacromoleculeName: RNA / type: rna / ID: 1 / Number of copies: 1
Source (natural)Organism: synthetic construct (others)
Molecular weightTheoretical: 168.106812 KDa
SequenceString: GCCCUCUCUA CACCUAUCGG UGUACCCAUA AGGGUCGCCC CAGAGAGGGC CCACUCACCG GGGCCACAGG GAGUGAAGGA CGGAACAAG UAUGGCGUUC GCGCCAUGCU UGAACCACCG UAUACCGAAC GGUACGUACG GUGGUGAAAC AAACAAAUAA A CUAAAUUA ...String:
GCCCUCUCUA CACCUAUCGG UGUACCCAUA AGGGUCGCCC CAGAGAGGGC CCACUCACCG GGGCCACAGG GAGUGAAGGA CGGAACAAG UAUGGCGUUC GCGCCAUGCU UGAACCACCG UAUACCGAAC GGUACGUACG GUGGUGAAAC AAACAAAUAA A CUAAAUUA UGUGUGCCCG GCAUGGGUGC AGUCUAUAGG GUGAGAGUCC CGAACUGUGA AGGCAGAAGU AACAGUUAGC CU AACGCAA GGGUGUCCGU GGCGACAUGG AAUCUGAAGG AAGCGGACGG CAAACCUUCG GUCUGAGGAA CACGAACUUC AUA UGAGGC UAGGUAUCAA UGGAUGAGUU UGCAUAACAA AACAAAGUCC UUUCUGCCAA AGUUGGUACA GAGUAAAUGA AGCA GAUUG AUGAAGGGAA AGACUGCAUU CUUACCCGGG GAGGUCUGAG CUUUCGAGCU CAGAAGUCAG CAGAAGUCAU AGUAA CUCC CUGUGCCGCC CCAAAGGGCG GAGUGAGUGG GGAUC

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Experimental details

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Structure determination

Methodcryo EM
Processingsingle particle reconstruction
Aggregation stateparticle

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Sample preparation

Concentration5 mg/mL
BufferpH: 6.5
VitrificationCryogen name: ETHANE-PROPANE

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Electron microscopy

MicroscopeTFS KRIOS
Image recordingFilm or detector model: TFS FALCON 4i (4k x 4k) / Average electron dose: 50.0 e/Å2
Electron beamAcceleration voltage: 300 kV / Electron source: FIELD EMISSION GUN
Electron opticsIllumination mode: FLOOD BEAM / Imaging mode: BRIGHT FIELD / Nominal defocus max: 2.0 µm / Nominal defocus min: 0.6 µm
Experimental equipment
Model: Titan Krios / Image courtesy: FEI Company

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Image processing

CTF correctionSoftware - Name: cryoSPARC / Type: PHASE FLIPPING AND AMPLITUDE CORRECTION
Startup modelType of model: INSILICO MODEL
Final reconstructionApplied symmetry - Point group: C1 (asymmetric) / Resolution.type: BY AUTHOR / Resolution: 4.7 Å / Resolution method: FSC 0.143 CUT-OFF / Software: (Name: cryoSPARC, PHENIX) / Number images used: 633764
Initial angle assignmentType: MAXIMUM LIKELIHOOD / Software - Name: cryoSPARC
Final angle assignmentType: MAXIMUM LIKELIHOOD / Software - Name: cryoSPARC
FSC plot (resolution estimation)

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