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- PDB-11ag: MPNN-RFdiff designed RNA molecule -

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Basic information

Entry
Database: PDB / ID: 11ag
TitleMPNN-RFdiff designed RNA molecule
ComponentsRNA (518-MER)
KeywordsRNA / pseudoknot / kissing multiloops
Function / homologyRNA / RNA (> 10) / RNA (> 100)
Function and homology information
Biological speciessynthetic construct (others)
MethodELECTRON MICROSCOPY / single particle reconstruction / cryo EM / Resolution: 4.8 Å
AuthorsHingey, J. / Spellmon, N. / Favor, A.H. / Kubaney, A. / Baker, D. / Haack, D.B. / Rudolfs, B. / Mancino, A. / Yu, Z. / Toor, N. / Das, R.
Funding support United States, 1items
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 13, 2026Deposition site: RCSB / Processing site: RCSB
Revision 1.0May 27, 2026Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: EM metadata / Data content type: EM metadata / Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: Additional map / Part number: 1 / Data content type: Additional map / Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: FSC / Data content type: FSC / Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: Half map / Part number: 1 / Data content type: Half map / Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: Half map / Part number: 2 / Data content type: Half map / Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: Image / Data content type: Image / Provider: repository / Type: Initial release
Revision 1.0May 27, 2026Data content type: Primary map / Data content type: Primary map / Provider: repository / Type: Initial release
Revision 1.1Sep 9, 2026Group: Data collection / Database references / Category: citation / citation_author / em_admin
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Revision 1.1Sep 9, 2026Data content type: EM metadata / Data content type: EM metadata / EM metadata / Group: Database references / Experimental summary / Data content type: EM metadata / EM metadata / EM metadata / Category: citation / citation_author / em_admin
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Structure visualization

Structure viewerMolecule:
MolmilJmol/JSmol

Downloads & links

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Assembly

Deposited unit
A: RNA (518-MER)
C: RNA (518-MER)


Theoretical massNumber of molelcules
Total (without water)335,9322
Polymers335,9322
Non-polymers00
Water00
1


  • Idetical with deposited unit
  • defined by author
  • Evidence: electron microscopy, not applicable
TypeNameSymmetry operationNumber
identity operation1_5551

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Components

#1: RNA chain RNA (518-MER)


Mass: 167965.844 Da / Num. of mol.: 2
Source method: isolated from a genetically manipulated source
Source: (gene. exp.) synthetic construct (others) / Production host: Escherichia phage T7 (virus)
Has protein modificationN

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Experimental details

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Experiment

ExperimentMethod: ELECTRON MICROSCOPY
EM experimentAggregation state: PARTICLE / 3D reconstruction method: single particle reconstruction

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Sample preparation

ComponentName: De novo design of RNA Kissing Multiloops using MPNN-RFdiff
Type: COMPLEX / Entity ID: all / Source: RECOMBINANT
Source (natural)Organism: synthetic construct (others)
Source (recombinant)Organism: Escherichia phage T7 (virus)
Buffer solutionpH: 6.5
SpecimenConc.: 5 mg/ml / Embedding applied: NO / Shadowing applied: NO / Staining applied: NO / Vitrification applied: YES
VitrificationCryogen name: ETHANE-PROPANE

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Electron microscopy imaging

Experimental equipment
Model: Titan Krios / Image courtesy: FEI Company
MicroscopyModel: TFS KRIOS
Electron gunElectron source: FIELD EMISSION GUN / Accelerating voltage: 300 kV / Illumination mode: FLOOD BEAM
Electron lensMode: BRIGHT FIELD / Nominal defocus max: 2000 nm / Nominal defocus min: 600 nm
Image recordingElectron dose: 50 e/Å2 / Film or detector model: TFS FALCON 4i (4k x 4k)

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Processing

EM software
IDNameVersionCategory
1cryoSPARCparticle selection
2PHENIX1.21.1_5286model refinement
3SerialEMimage acquisition
5cryoSPARCCTF correction
10cryoSPARCinitial Euler assignment
11cryoSPARCfinal Euler assignment
13cryoSPARC3D reconstruction
14PHENIX3D reconstruction
CTF correctionType: PHASE FLIPPING AND AMPLITUDE CORRECTION
SymmetryPoint symmetry: C2 (2 fold cyclic)
3D reconstructionResolution: 4.8 Å / Resolution method: FSC 0.143 CUT-OFF / Num. of particles: 115837 / Symmetry type: POINT
RefinementHighest resolution: 4.8 Å
Stereochemistry target values: REAL-SPACE (WEIGHTED MAP SUM AT ATOM CENTERS)
Refine LS restraints
Refine-IDTypeDev idealNumber
ELECTRON MICROSCOPYf_bond_d0.0024852
ELECTRON MICROSCOPYf_angle_d0.5397562
ELECTRON MICROSCOPYf_dihedral_angle_d27.863096
ELECTRON MICROSCOPYf_chiral_restr0.0231010
ELECTRON MICROSCOPYf_plane_restr0.004202

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