ArticleNature methods2023
CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning.
Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed, 45 citations in OpenAlex.
- Nucleic acid aptamers: new methods for selection, target validation, molecular diagnostics and therapeutics.Signal transduction and targeted therapy · 2026Review
- Computational Approaches for Protein-DNA/RNA Complex Modeling for Cryo-EM Maps.Current protocols · 2026Article
- Direct Detection and Atomic Modeling of Ligands in Cryo-EM Maps Using Deep Learning.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking deep learning methods for Cα atom prediction in cryo-EM density maps.Bioinformatics (Oxford, England) · 2026Article
- DNA deformability in sequence-dependent capture of E. coli gyrase.Nature communications · 2026Article
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
- ChironRNA: Steric Clashes Resolution in RNA Structures via E(3)-Equivariant Diffusion.bioRxiv : the preprint server for biology · 2026Article
- Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta.bioRxiv : the preprint server for biology · 2026Article
- Integrated experimental and AI innovations for RNA structure determination.Nature biotechnology · 2026Review
- CryoAtom improves model building for cryo-EM.Nature structural & molecular biology · 2026Article
- RAD51 D-loop structures reveal the mechanism of eukaryotic RAD51-mediated strand exchange.Nature communications · 2025Article
- CryoDataBot: a pipeline to curate cryoEM datasets for AI-driven structural biology.bioRxiv : the preprint server for biology · 2025Article
- MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures.Nature communications · 2025Article
- Structural basis of circularly permuted group II intron self-splicing.Nature structural & molecular biology · 2025Article
- RNA sample optimization for cryo-EM analysis.Nature protocols · 2025Review
- Molecular basis of foreign DNA recognition by BREX anti-phage immunity system.Nature communications · 2025Article
- Advancing structure modeling from cryo-EM maps with deep learning.Biochemical Society transactions · 2025Review
- AI-based methods for biomolecular structure modeling for Cryo-EM.Current opinion in structural biology · 2025Review
- CryoDataBot: a pipeline to curate cryoEM datasets for AI-driven structural biology.GigaScience · 2025Article
- Secondary Structure Detection and Structure Modeling for Cryo-EM.Methods in molecular biology (Clifton, N.J.) · 2025Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to understanding the molecular mechanisms of their functions. Although an increasing number of nucleic acid structures and their complexes with proteins are determined by cryogenic electron microscopy (cryo-EM), structure modeling for DNA and RNA remains challenging particularly when the map is determined at a resolution coarser than atomic level. Moreover, computational methods for nucleic acid structure modeling are relatively scarce. Here, we present CryoREAD, a fully automated de novo DNA/RNA atomic structure modeling method using deep learning. CryoREAD identifies phosphate, sugar and base positions in a cryo-EM map using deep learning, which are traced and modeled into a three-dimensional structure. When tested on cryo-EM maps determined at 2.0 to 5.0 Å resolution, CryoREAD built substantially more accurate models than existing methods. We also applied the method to cryo-EM maps of biomolecular complexes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
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