ArticleProtein science : a publication of the Protein Society2023
DPAM: A domain parser for AlphaFold models.
Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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38 citing papers in PubMed.
- Microbial GAIN domains undergo autoproteolysis and enable release of diverse cell-surface-associated proteins.Current biology : CB · 2026Article
- Domain classification of archaeal proteomes reveals conserved fold repertoire.PLoS computational biology · 2026Article
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- T3SS effector and regulator discovery by predicting interacting partners of T3SS chaperones in Pseudomonas aeruginosa.Protein science : a publication of the Protein Society · 2026Article
- Bacterial Schlafen proteins mediate phage defence.Nature microbiology · 2026Article
- ECOD: Classification of domains in AFDB Swiss-Prot structure predictions.PLoS computational biology · 2026Article
- Exploring the Terra incognita of AI-based domain classifications.Protein science : a publication of the Protein Society · 2025Article
- Using evolutionary context to classify difficult protein folds.PLoS computational biology · 2025Article
- AFragmenter: schema-free, tuneable protein domain segmentation for AlphaFold protein structures.Bioinformatics (Oxford, England) · 2025Article
- Predicting protein-protein interactions in the human proteome.Science (New York, N.Y.) · 2025Article
- SPAED: harnessing AlphaFold output for accurate segmentation of phage endolysin domains.Bioinformatics (Oxford, England) · 2025Article
- The CAGE complex: a hollow, megadalton, protein assembly in prokaryotic and eukaryotic microbes.bioRxiv : the preprint server for biology · 2025Article
- Assessing Structural Classification Using AlphaFold2 Models Through ECOD-Based Comparative Analysis.Proteins · 2025Article
- Unveiling the hidden interactome of CRBN molecular glues.Nature communications · 2025Article
- Bacterial Schlafens mediate anti-phage defense.bioRxiv : the preprint server for biology · 2025Article
- 3-D substructure search by transitive closure in AlphaFold database.Protein science : a publication of the Protein Society · 2025Article
- Easy and accurate protein structure prediction using ColabFold.Nature protocols · 2025Review
- Refinement and curation of homologous groups facilitated by structure prediction.Protein science : a publication of the Protein Society · 2025Article
- A structural atlas of death domain fold proteins reveals their versatile roles in biology and function.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- DPAM-AI: a domain parser for AlphaFold models powered by artificial intelligence.Bioinformatics (Oxford, England) · 2024Article
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5 authors.
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Abstract
The recent breakthroughs in structure prediction, where methods such as AlphaFold demonstrated near-atomic accuracy, herald a paradigm shift in structural biology. The 200 million high-accuracy models released in the AlphaFold Database are expected to guide protein science in the coming decades. Partitioning these AlphaFold models into domains and assigning them to an evolutionary hierarchy provide an efficient way to gain functional insights into proteins. However, classifying such a large number of predicted structures challenges the infrastructure of current structure classifications, including our Evolutionary Classification of protein Domains (ECOD). Better computational tools are urgently needed to parse and classify domains from AlphaFold models automatically. Here we present a Domain Parser for AlphaFold Models (DPAM) that can automatically recognize globular domains from these models based on inter-residue distances in 3D structures, predicted aligned errors, and ECOD domains found by sequence (HHsuite) and structural (Dali) similarity searches. Based on a benchmark of 18,759 AlphaFold models, we demonstrate that DPAM can recognize 98.8% of domains and assign correct boundaries for 87.5%, significantly outperforming structure-based domain parsers and homology-based domain assignment using ECOD domains found by HHsuite or Dali. Application of DPAM to the massive AlphaFold models will enable efficient classification of domains, providing evolutionary contexts and facilitating functional studies.
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