NatureBioinformaticsPeer-reviewed journal article
Sequence clustering confounds AlphaFold2
Joseph W. SchaferiD, Myeongsang LeeiD, Devlina ChakravartyiD, Joseph F. TholeiD, Ethan A. Chen, Lauren L. PorteriD
Abstract
Though typically associated with a single folded state, some globular proteins remodel their secondary and/or tertiary structures in response to cellular stimuli. AlphaFold21 (AF2) readily generates one dominant protein structure for these fold-switching (a.k.a. metamorphic) proteins2, but it often fails to predict their alternative experimentally observed structures3,4. Wayment-Steele, et al. steered AF2 to predict alternative structures of a few metamorphic proteins using a method they call AF-cluster5. However, their Paper lacks some essential controls needed to assess AF-clusters reliability. We find that these controls show AF-cluster to be a poor predictor of metamorphic proteins. First, closer examination of the Papers results reveals that random sequence sampling outperforms sequence clustering, challenging the claim that AF-cluster works by "deconvolving conflicting sets of couplings." Further, we observe that AF-cluster mistakes some single-folding KaiB homologs for fold switchers, a critical flaw bound to mislead users. Finally, proper error analysis reveals that AF-cluster predicts many correct structures with low confidence and some experimentally unobserved conformations with confidences similar to experimentally observed ones. For these reasons, we suggest using ColabFold6-based random sequence sampling7-augmented by other predictive approaches-as a more accurate and less computationally intense alternative to AF-cluster.
- assay: protein structure
- research focus: benchmarking
- research focus: protein structure prediction
- approach: deep learning
- approach: statistical model
- Citations
- 38
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- AlphaFold2's training set powers its predictions of fold-switched conformations
Joseph W. Schafer, Lauren L. Porter·bioRxiv·Oct 11, 2024
- Prediction of multiple conformational states by combining sequence clustering with AlphaFold2
H. K. Wayment-Steele, S. Ovchinnikov, … D. Kern·bioRxiv·Oct 17, 2022
- AlphaFold2 fails to predict protein fold switching
Devlina Chakravarty, Lauren L. Porter·Protein SciencePeer-reviewed·May 26, 2022
- Does Sequence Clustering Confound AlphaFold2?
Hannah K. Wayment-Steele, Sergey Ovchinnikov, … Dorothee Kern·Journal of Molecular BiologyPeer-reviewed·Aug 6, 2025
- AlphaFold2 has more to learn about protein energy landscapes
Devlina Chakravarty, Joseph W. Schafer, … Lauren L. Porter·Nature CommunicationsPeer-reviewed·Aug 24, 2024
- Colabfold predicts alternative protein structures from single sequences, coevolution unnecessary for AF-cluster
Lauren L. Porter, Devlina Chakravarty, … Ethan A. Chen·bioRxiv·Nov 21, 2023