Evidence map›Paper›PMID 35634782›Full record

ArticleProtein science : a publication of the Protein Society2022

AlphaFold2 fails to predict protein fold switching.

Devlina Chakravarty, Lauren L Porter

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
119citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

119 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Fold-Switching Proteins.Annual review of biophysics · 2026
    Review
  13. Exploring PadR Proteins for Artificial Enzyme Design.Chembiochem : a European journal of chemical biology · 2026
    Article
  14. Article
  15. 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 · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

59 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Devlina ChakravartyNational Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, USA.
Lauren L PorterNational Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0003-2031-8326

Funding

Predictions and experimental validation of fold-switching proteinsZIALM202011 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PORTER, LAUREN · 2020 to 2025
$6.5M
6 · The paper itself

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.

Indexed as

Intrinsically Disordered ProteinsSequence AlignmentIntrinsically Disordered ProteinsAlphaFold2fold-switchingprotein-foldingstructural heterogeneity

Identifiers

PMID35634782
PMCPMC9134877

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.