ArticleNature communications2022
Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
- MultilevelCurrent research in structural biology · 2026Article
- EMReady2: improvement of cryo-EM and cryo-ET maps by local quality-aware deep learning with Mamba.Nature communications · 2026Article
- A Novel Machine-Learning Based Method for Resolving Secondary Structure Topology in Medium-Resolution Cryo-EM Density Maps.International journal of molecular sciences · 2026Article
- Structural atlas of the intact jumbo phage phiKZ.Nature communications · 2026Article
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
- Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta.bioRxiv : the preprint server for biology · 2026Article
- When cryo-EM modeling meets structure prediction.Nature structural & molecular biology · 2026Article
- CryoAtom improves model building for cryo-EM.Nature structural & molecular biology · 2026Article
- EMProt improves structure determination from cryo-EM maps.Nature structural & molecular biology · 2026Article
- Advances in Crystallography and Cryo-Electron Microscopy for the Study of Membrane Proteins.Advances in experimental medicine and biology · 2026Review
- Impurities in amyloid studies: The power of automated model building within a cautionary tale for structural biologists.Protein science : a publication of the Protein Society · 2025Article
- Unraveling the Obesogenic Mechanism of Bisphenol A Through Network Toxicology and Molecular Docking: Identification of Key Molecular Targets.International journal of molecular sciences · 2025Article
- Modeling cryo-EM structures in alternative states with AlphaFold2-based models and density-guided simulations.Communications chemistry · 2025Article
- Accurate Protein Dynamic Conformational Ensembles: Combining AlphaFold, MD, and AmideInternational journal of molecular sciences · 2025Article
- DEMO-EMol: modeling protein-nucleic acid complex structures from cryo-EM maps by coupling chain assembly with map segmentation.Nucleic acids research · 2025Article
- A comprehensive survey and benchmark of deep learning-based methods for atomic model building from cryo-electron microscopy density maps.Briefings in bioinformatics · 2025Article
- Advancing structure modeling from cryo-EM maps with deep learning.Biochemical Society transactions · 2025Review
- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- Connecting the dots: deep learning-based automated model building methods in cryo-EM.Frontiers in molecular biosciences · 2025Review
- Article
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5 authors.
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Abstract
Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-electron microscopy (cryo-EM) maps. However, building accurate models into intermediate-resolution EM maps remains challenging and labor-intensive. Here, we propose an automatic model building method of multi-chain protein complexes from intermediate-resolution cryo-EM maps, named EMBuild, by integrating AlphaFold structure prediction, FFT-based global fitting, domain-based semi-flexible refinement, and graph-based iterative assembling on the main-chain probability map predicted by a deep convolutional network. EMBuild is extensively evaluated on diverse test sets of 47 single-particle EM maps at 4.0-8.0 Å resolution and 16 subtomogram averaging maps of cryo-ET data at 3.7-9.3 Å resolution, and compared with state-of-the-art approaches. We demonstrate that EMBuild is able to build high-quality complex structures that are comparably accurate to the manually built PDB structures from the cryo-EM maps. These results demonstrate the accuracy and reliability of EMBuild in automatic model building.
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