ArticleActa crystallographica. Section D, Structural biology2025
Categorizing prediction modes within low-pLDDT regions of AlphaFold2 structures: near-predictive, pseudostructure and barbed wire.
Article in Acta crystallographica. Section D, Structural biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Comparative Sequence-Structural Analysis of TdNV-Korea Entry Factors Identifies Candidate Regions Associated with Host-Range Variation.International journal of molecular sciences · 2026Article
- Discovery of a sulfotyrosine-motif in the human TrkB extracellular domain required for agonist activation.bioRxiv : the preprint server for biology · 2026Article
- The Chromaverse Is Colored by Triplexes Formed Through the Interactions of Noncoding RNAs with HNPRNPU, TP53, AGO, REL Proteins, Intrinsically-Disordered Regions, and Flipons.International journal of molecular sciences · 2026Article
- Evaluating transformer-based models for structural characterization of orphan proteins.Bioinformatics advances · 2026Article
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Abstract
AlphaFold2 protein structure predictions are widely available for structural biology uses. These predictions, especially for eukaryotic proteins, frequently contain extensive regions predicted below the pLDDT = 70 level, the rule-of-thumb cutoff for high confidence. This work identifies major modes of behavior within low-pLDDT regions through a survey of human proteome predictions provided by the AlphaFold Protein Structure Database. The near-predictive mode resembles folded protein and can be a nearly accurate prediction. Barbed wire is extremely unprotein-like, being recognized by wide looping coils, an absence of packing contacts and numerous signature validation outliers, and it represents a region where the conformation has no predictive value. Pseudostructure presents an intermediate behavior with a misleading appearance of isolated and badly formed secondary-structure-like elements. These prediction modes are compared with annotations of disorder from MobiDB, showing general correlation between barbed wire/pseudostructure and many measures of disorder, an association between pseudostructure and signal peptides, and an association between near-predictive and regions of conditional folding. To enable users to identify these regions within a prediction, a new Phenix tool is developed encompassing the results of this work, including prediction annotation, visual markup and residue selection based on these prediction modes. This tool will help users develop expertise in interpreting difficult AlphaFold predictions and identify the near-predictive regions that can aid in molecular replacement when a prediction does not contain enough high-pLDDT regions.
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