ArticleNature2026
Atomically accurate de novo design of antibodies with RFdiffusion.
Article in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers.
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.
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.
Who cites it
123 citing papers in PubMed.
- Article
- NanoSaurus: addressing the urgent need for open access in single-domain antibody research.mAbs · 2026Article
- Programming biological behavior with AI-guided de novo protein design.Molecular cell · 2026Review
- Computational design of metalloproteases.Nature · 2026Article
- DESIGN: a framework for generative AI-enabled crop molecular design-driven breeding.Science China. Life sciences · 2026Review
- Computational design and translational development of TCR-mimic scFv antibodies for peptide-HLA neoantigen targeting.npj drug discovery · 2026Review
- Multiobjective VScience advances · 2026Article
- Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- Antibody-drug conjugate engineering: from design to efficacy and safety.Signal transduction and targeted therapy · 2026Review
- Evolutionary Dynamics-AwareACS omega · 2026Article
- Big Data and Artificial Intelligence in Cancer Drug Discovery: Promise, Challenges, and Emerging Opportunities.Cancers · 2026Review
- De novo generation and computational screening of dual-targeting short peptide inhibitors against PBP2b and PBP2x in drug-resistant Streptococcus Pneumoniae.Molecular diversity · 2026Article
- The Evolution of Artificial Intelligence in Antibody Design: From Structure-Based Engineering to Generative Models.Antibodies (Basel, Switzerland) · 2026Review
- Discovery of TCR-like antibodies to the KRAS G12D neoantigen via in silico-in vitro workflow.Molecular therapy : the journal of the American Society of Gene Therapy · 2026Article
- Nanobodies Open New Avenues in Cancer Treatment: From Molecular Engineering to Therapeutic Platforms.Cell biochemistry and biophysics · 2026Review
- AVIDbase: A biologically accurate structural dataset of nanobody-antigen complexes.Protein science : a publication of the Protein Society · 2026Article
- Review
- A systematic evaluation framework for universal antibody-antigen binding affinity prediction and candidate recommendation.iScience · 2026Article
- Advances in Carrageenases: Molecular Engineering, Immobilization Techniques, and Biomedical Potential of Carrageenan Oligosaccharides.Marine drugs · 2026Review
- Accelerating protein design by scaling experimental characterization.Nature communications · 2026Article
63 more citing papers are in PubMed but not listed here.
Corrections and comments
- Update of
Authors and funding
32 authors.
Funding
Abstract
Despite the central role of antibodies in modern medicine, no method currently exists to design novel, epitope-specific antibodies entirely in silico. Instead, antibody discovery currently relies on immunization, random library screening or the isolation of antibodies directly from patients
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.