ArticleNature communications2018
De novo main-chain modeling for EM maps using MAINMAST.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.
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Who cites it
76 citing papers in PubMed, 148 citations in OpenAlex.
- CryoTriplane: triplane-based neural radiance field representation for high-resolution cryo-EM 3D homogeneous reconstruction.Bioinformatics (Oxford, England) · 2026Article
- Computational Approaches for Protein-DNA/RNA Complex Modeling for Cryo-EM Maps.Current protocols · 2026Article
- Benchmarking deep learning methods for Cα atom prediction in cryo-EM density maps.Bioinformatics (Oxford, England) · 2026Article
- Accurate Macromolecular Complex Modeling for Cryo-EM with CryoZeta.bioRxiv : the preprint server for 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
- 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
- Multimodal deep learning integration of cryo-EM and AlphaFold3 for high-accuracy protein structure determination.Communications chemistry · 2025Article
- Recognizing amino acid sidechains in a medium-resolution cryo-electron density map.Protein science : a publication of the Protein Society · 2025Article
- DEMO-EMol: modeling protein-nucleic acid complex structures from cryo-EM maps by coupling chain assembly with map segmentation.Nucleic acids research · 2025Article
- Ensemble refinement of mismodeled cryo-EM RNA structures using all-atom simulations.Nature communications · 2025Article
- A Labeled Dataset for AI-based Cryo-EM Map Enhancement.bioRxiv : the preprint server for biology · 2025Article
- CryoTEN: efficiently enhancing cryo-EM density maps using transformers.Bioinformatics (Oxford, England) · 2025Article
- MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025Review
- 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
- All-atom RNA structure determination from cryo-EM maps.Nature biotechnology · 2025Article
- Connecting the dots: deep learning-based automated model building methods in cryo-EM.Frontiers in molecular biosciences · 2025Review
- Secondary Structure Detection and Structure Modeling for Cryo-EM.Methods in molecular biology (Clifton, N.J.) · 2025Article
- A labeled dataset for AI-based cryo-EM map enhancement.Computational and structural biotechnology journal · 2025Article
16 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
An increasing number of protein structures are determined by cryo-electron microscopy (cryo-EM) at near atomic resolution. However, tracing the main-chains and building full-atom models from EM maps of ~4-5 Å is still not trivial and remains a time-consuming task. Here, we introduce a fully automated de novo structure modeling method, MAINMAST, which builds three-dimensional models of a protein from a near-atomic resolution EM map. The method directly traces the protein's main-chain and identifies Cα positions as tree-graph structures in the EM map. MAINMAST performs significantly better than existing software in building global protein structure models on data sets of 40 simulated density maps at 5 Å resolution and 30 experimentally determined maps at 2.6-4.8 Å resolution. In another benchmark of building missing fragments in protein models for EM maps, MAINMAST builds fragments of 11-161 residues long with an average RMSD of 2.68 Å.
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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.