ArticleProtein science : a publication of the Protein Society2022
AlphaFold2 fails to predict protein fold switching.
Article in Protein science : a publication of the Protein Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 119 papers.
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119 citing papers in PubMed.
- Article
- Several multiple sequence alignment-perturbing methods enhance AlphaFold3 sampling of alternative protein states.Communications chemistry · 2026Article
- Hierarchical discrete representations for coarse-to-fine protein conformation generation.Bioinformatics (Oxford, England) · 2026Article
- Review
- Explainable AI reveals the allosteric blind spot in protein-ligand binding predictions.Cell reports. Physical science · 2026Article
- Deciphering the Function and Structure of PA1216 as an S-Adenosyl-l-Methionine Binding Protein Using Differential Scanning Fluorimetry and Circular Dichroism.Protein science : a publication of the Protein Society · 2026Article
- Navigating the uncharted: AI-driven advances in protein structure, dynamics, interactions and ligand interactions for understudied families.BioData mining · 2026Review
- Bridging structure and function: artificial intelligence-based modelling of kidney proteins.Nature reviews. Nephrology · 2026Review
- AlphaInterp: Mechanistic Interpretability of AlphaFold 3 Reveals How Evolutionary Information Shapes Protein Structure Prediction.bioRxiv : the preprint server for biology · 2026Article
- The intrinsic disorder challenge for AlphaFold: A case study of G3BP1 and pathogenic peptide.iScience · 2026Article
- Thermodynamic prediction of RNA cellular activity from sequence via conformational ensembles.Cell · 2026Article
- Fold-Switching Proteins.Annual review of biophysics · 2026Review
- Exploring PadR Proteins for Artificial Enzyme Design.Chembiochem : a European journal of chemical biology · 2026Article
- Exploration of the structural and functional diversity in the metamorphic RfaH subfamily.bioRxiv : the preprint server for biology · 2026Article
- Bias in the AlphaFold3 prediction of ligand-induced domain motion in enzymes.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Disentangling coevolutionary constraints for modeling protein conformational heterogeneity.Communications chemistry · 2026Article
- Article
- A fold switch regulates conformation of an alphavirus RNA-dependent RNA polymerase.Nucleic acids research · 2026Article
- Article
- Predicted protein 3D structures provide essential insights into the genetic architecture underlying phenotypic diversity in maize.Genome research · 2026Article
59 more citing papers are in PubMed but not listed here.
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2 authors.
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Abstract
AlphaFold2 has revolutionized protein structure prediction by leveraging sequence information to rapidly model protein folds with atomic-level accuracy. Nevertheless, previous work has shown that these predictions tend to be inaccurate for structurally heterogeneous proteins. To systematically assess factors that contribute to this inaccuracy, we tested AlphaFold2's performance on 98-fold-switching proteins, which assume at least two distinct-yet-stable secondary and tertiary structures. Topological similarities were quantified between five predicted and two experimentally determined structures of each fold-switching protein. Overall, 94% of AlphaFold2 predictions captured one experimentally determined conformation but not the other. Despite these biased results, AlphaFold2's estimated confidences were moderate-to-high for 74% of fold-switching residues, a result that contrasts with overall low confidences for intrinsically disordered proteins, which are also structurally heterogeneous. To investigate factors contributing to this disparity, we quantified sequence variation within the multiple sequence alignments used to generate AlphaFold2's predictions of fold-switching and intrinsically disordered proteins. Unlike intrinsically disordered regions, whose sequence alignments show low conservation, fold-switching regions had conservation rates statistically similar to canonical single-fold proteins. Furthermore, intrinsically disordered regions had systematically lower prediction confidences than either fold-switching or single-fold proteins, regardless of sequence conservation. AlphaFold2's high prediction confidences for fold switchers indicate that it uses sophisticated pattern recognition to search for one most probable conformer rather than protein biophysics to model a protein's structural ensemble. Thus, it is not surprising that its predictions often fail for proteins whose properties are not fully apparent from solved protein structures. Our results emphasize the need to look at protein structure as an ensemble and suggest that systematic examination of fold-switching sequences may reveal propensities for multiple stable secondary and tertiary structures.
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