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NatureBioinformaticsPeer-reviewed journal article

Sequence clustering confounds AlphaFold2

Joseph W. SchaferiD, Myeongsang LeeiD, Devlina ChakravartyiD, Joseph F. TholeiD, Ethan A. Chen, Lauren L. PorteriD

PDFDOIPreprint

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.

Citations
38

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Joseph W. Schafer, Lauren L. Porter·bioRxiv·Oct 11, 2024· 5 citations