ArticleNature methods2024
Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Confidence-guided cryo-EM map optimisation with LocScale-2.0.Nature communications · 2026Article
- Developments and challenges in hit progression within fragment-based drug discovery.Nature communications · 2026Review
- Q-score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps.Acta crystallographica. Section D, Structural biology · 2025Article
- InstaMap: instant-NGP for cryo-EM density maps.Acta crystallographica. Section D, Structural biology · 2025Article
- MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025Review
- High-resolution protein modeling through Cryo-EM and AI: current trends and future perspectives - a review.Frontiers in molecular biosciences · 2025Review
- Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches.npj drug discovery · 2025Review
- Ligand identification in CryoEM and X-ray maps using deep learning.Bioinformatics (Oxford, England) · 2024Article
- Ligand Identification in CryoEM and X-ray Maps Using Deep Learning.bioRxiv : the preprint server for biology · 2024Article
- Toward learning a foundational representation of cells and genes.Nature methods · 2024Article
- Embedding AI in biology.Nature methods · 2024Article
- De novo atomic protein structure modeling for cryoEM density maps using 3D transformer and HMM.Nature communications · 2024Article
- Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases.Clinical reviews in allergy & immunology · 2024Review
- Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures.Scientific data · 2024Article
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81 authors.
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Abstract
The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein-nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.
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