ArticleActa crystallographica. Section D, Structural biology2023
Protein model refinement for cryo-EM maps using AlphaFold2 and the DAQ score.
Article in Acta crystallographica. Section D, Structural biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Structural Characterization of Native RNA Polymerase II Transcription Complexes and Nucleosomes in Drosophila melanogaster.Nature communications · 2026Article
- Computational Approaches for Protein-DNA/RNA Complex Modeling for Cryo-EM Maps.Current protocols · 2026Article
- Modeling cryo-EM structures in alternative states with AlphaFold2-based models and density-guided simulations.Communications chemistry · 2025Article
- AI-based quality assessment methods for protein structure models from cryo-EM.Current research in structural biology · 2025Review
- AlphaFold two years on: Validation and impact.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Unveiling the stochastic nature of human heteropolymer ferritin self-assembly mechanism.Protein science : a publication of the Protein Society · 2024Article
- Dynamic Changes in Ion Channels during Myocardial Infarction and Therapeutic Challenges.International journal of molecular sciences · 2024Review
- Predictive modeling and cryo-EM: A synergistic approach to modeling macromolecular structure.Biophysical journal · 2024Review
- Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels.International journal of molecular sciences · 2023Review
- Automated identification of chalcogen bonds in AlphaFold protein structure database files: is it possible?Frontiers in molecular biosciences · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
As more protein structure models have been determined from cryogenic electron microscopy (cryo-EM) density maps, establishing how to evaluate the model accuracy and how to correct models in cases where they contain errors is becoming crucial to ensure the quality of the structural models deposited in the public database, the PDB. Here, a new protocol is presented for evaluating a protein model built from a cryo-EM map and applying local structure refinement in the case where the model has potential errors. Firstly, model evaluation is performed using a deep-learning-based model-local map assessment score, DAQ, that has recently been developed. The subsequent local refinement is performed by a modified AlphaFold2 procedure, in which a trimmed template model and a trimmed multiple sequence alignment are provided as input to control which structure regions to refine while leaving other more confident regions of the model intact. A benchmark study showed that this protocol, DAQ-refine, consistently improves low-quality regions of the initial models. Among 18 refined models generated for an initial structure, DAQ shows a high correlation with model quality and can identify the best accurate model for most of the tested cases. The improvements obtained by DAQ-refine were on average larger than other existing methods.
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