Evidence map›Paper›PMID 42658941›Full record

ArticleScience (New York, N.Y.)2026

De novo design of RNA pseudoknots with deep learning.

Jill Townley, Wipapat Kladwang, David Baker, Hamish M Blair, Christian A Choe, Gina El Nesr, Andrew Favor, Eli Fisker, Daniel B Haack, Shujun He and 17 more

Abstract read
PubMed Publisher
In one paragraph

Article in Science (New York, N.Y.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

27 authors.

Jill Townley *Eterna Massive Open Laboratory, USA.
Wipapat Kladwang *Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0009-0001-0490-9495
David BakerDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID 0000-0001-7896-6217
Hamish M BlairDepartment of Mathematics, Stanford University, Stanford, CA, USA.ORCID 0009-0000-0091-2032
Christian A ChoeDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID 0000-0001-8871-9682
Gina El NesrBiophysics Program, Stanford University, Stanford, CA, USA.ORCID 0000-0003-4857-9464
Andrew FavorDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID 0000-0002-9977-2785
Eli FiskerEterna Massive Open Laboratory, USA.ORCID 0000-0003-4703-717X
Daniel B HaackDepartment of Biochemistry and Molecular Biophysics University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-4926-7772
Shujun HeTexas A&M University, College Station, TX, USA.ORCID 0000-0003-1010-536X
Jason HingeyA-Form Solutions, Inc., San Diego, CA, USA.ORCID 0009-0004-1086-3421
Po-Ssu HuangDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID 0000-0002-7948-2895
Rui HuangDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0009-0009-6136-8013
Chaitanya K JoshiDepartment of Computer Science and Technology, University of Cambridge, UK.ORCID 0000-0003-4722-1815
Thomas KaragianesEterna Massive Open Laboratory, USA.ORCID 0009-0004-9872-1339
Andrew KubaneyDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID 0009-0009-4982-6050
Pietro LiòDepartment of Computer Science and Technology, University of Cambridge, UK.ORCID 0000-0002-0540-5053
Adamo MancinoJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.ORCID 0000-0002-4756-8782
Jonathan RomanoEterna Massive Open Laboratory, USA.ORCID 0000-0003-4031-0102
Boris RudolfsDepartment of Biochemistry and Molecular Biophysics University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-8791-9487
Nicholas SpellmonJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.ORCID 0000-0002-2045-1373
Navtej ToorDepartment of Biochemistry and Molecular Biophysics University of California San Diego, La Jolla, CA, USA.ORCID 0000-0002-6134-163X
Jigyasa VermaDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-9286-0299
Vivian WuDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0009-0000-6122-2457
Zhiheng YuJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.ORCID 0000-0002-7114-2570
Eterna ParticipantsEterna Massive Open Laboratory, USA.
Rhiju DasDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0001-7497-0972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 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.

Indexed as

Deep LearningNucleic Acid ConformationRNACryoelectron MicroscopyGenerative Artificial IntelligenceHumansModels, MolecularRNA FoldingRNA

Identifiers

PMID42658941

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.