ArticleNature2021
De novo protein design by deep network hallucination.
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In one paragraph
Article in Nature, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 286 papers.
0numbers the graph read from it
0cells of the map it votes in
286citing papers in PubMed
34.6field-weighted citation impact, top 1% of its field
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
286 citing papers in PubMed, 577 citations in OpenAlex.
- HURDLER: a cloning method to overcome length limits in designed repeat proteins.Nucleic acids research · 2026Article
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- AI-Designed TREM1-Targeted LYTAC Nanoparticles Reprogram the Neuroimmune Microenvironment in Traumatic Brain Injury.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Sequence and structural determinants of efficacious de novo chimaeric antigen receptors.Nature biomedical engineering · 2026Article
- De novo generation and computational screening of dual-targeting short peptide inhibitors against PBP2b and PBP2x in drug-resistant Streptococcus Pneumoniae.Molecular diversity · 2026Article
- Scalable Production of aPharmaceutics · 2026Article
- Aligning protein-generative models to experimental fitness with ProteinDPO.Nature methods · 2026Article
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- Accelerating protein design by scaling experimental characterization.Nature communications · 2026Article
- Discovery and design of potent cell surface display elements.Nature biotechnology · 2026Article
- Barley HvBODYGUARD1 controls cuticular specialisations regulated by SHINE transcription factors.The New phytologist · 2026Article
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Applications and limitations of AI tools in enzyme design.Protein science : a publication of the Protein Society · 2026Review
- Bridging Algorithms and Biocatalysis: Perspectives on AI-Supported Enzyme Engineering.Molecules (Basel, Switzerland) · 2026Review
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- Protein design and RNA design: Perspectives.Quantitative biology (Beijing, China) · 2026Article
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- A Paradigm Shift in Snakebite Envenoming Therapy: From Conventional Antivenoms to Rationally Designed, Broadly Neutralizing Combination Therapies.ACS pharmacology & translational science · 2026Review
- Scaffold-Lab: Critical evaluation and ranking of protein backbone generation methods in a unified framework.PLoS computational biology · 2026Article
226 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
15 authors at 4 institutions in 1 country.
Ivan Anishchenko *Department of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0003-3645-2044
Samuel J Pellock *Department of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-7557-7985
Tamuka M ChidyausikuDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-2561-782X
Theresa A RamelotDepartment of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, USA.ORCID http://orcid.org/0000-0002-0335-1573
Sergey OvchinnikovJohn Harvard Distinguished Science Fellowship Program, Harvard University, Cambridge, MA, USA.ORCID http://orcid.org/0000-0003-2774-2744
Jingzhou HaoDepartment of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, USA.
Khushboo BafnaDepartment of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, USA.ORCID http://orcid.org/0000-0002-1893-1175
Christoffer NornDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-1450-4651
Alex KangDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Asim K BeraDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-9473-2912
Frank DiMaioDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Lauren CarterDepartment of Biochemistry, University of Washington, Seattle, WA, USA.
Cameron M ChowDepartment of Biochemistry, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0001-5351-6412
Gaetano T MontelioneDepartment of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, USA.ORCID http://orcid.org/0000-0002-9440-3059
David BakerDepartment of Biochemistry, University of Washington, Seattle, WA, USA. dabaker@uw.edu.ORCID http://orcid.org/0000-0001-7896-6217
University of Washington · USRensselaer Polytechnic Institute · USHarvard University Press · USHoward Hughes Medical Institute · US
Funding
User Training and OutreachP30GM124165 · NIGMS · CORNELL UNIVERSITY · PI Nozomi Ando, J Christopher Fromme · 2018 to 2026
$34.2MHybrid Methods for Dynamic Structure Analysis of Proteins from Pathogenic MicroorganismsR35GM141818 · NIGMS · RENSSELAER POLYTECHNIC INSTITUTE · PI MONTELIONE, GAETANO T · 2021 to 2025
$3.3MMembrane Protein Structure Using Evolutionary Couplings and Sparse NMR DataR01GM120574 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI MONTELIONE, GAETANO T · 2017 to 2020
$2.3MExploring the unknown protein universe using evolutionary informationDP5OD026389 · OD · HARVARD UNIVERSITY · PI OVCHINNIKOV, SERGEY L. · 2018 to 2022
$2.0MPixel Array Detector for Macromolecular CrystallographyS10OD021527 · OD · CORNELL UNIVERSITY · PI EALICK, STEVEN E · 2016 to 2016
$2.0MHoward Hughes Medical InstituteNIGMS NIH HHS P30 GM124165NIGMS NIH HHS R01 GM120574NIGMS NIH HHS R35 GM141818NIH HHS DP5 OD026389NIH HHS S10 OD021527
Abstract
There has been considerable recent progress in protein structure prediction using deep neural networks to predict inter-residue distances from amino acid sequences
Indexed as
Neural Networks, ComputerProteinsAmino Acid SequenceCrystallography, X-RayHallucinationsHumansProtein ConformationProteins
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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.