Predicting multiple conformations via sequence clustering and AlphaFold2

Hannah K. Wayment-Steele, Adedolapo Ojoawo, Renee Otten, Julia M. Apitz, Warintra Pitsawong, Marc Hömberger, Sergey Ovchinnikov, Lucy Colwell and Dorothee Kern ()
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Hannah K. Wayment-Steele: Brandeis University and Howard Hughes Medical Institute
Adedolapo Ojoawo: Brandeis University and Howard Hughes Medical Institute
Renee Otten: Brandeis University and Howard Hughes Medical Institute
Julia M. Apitz: Brandeis University and Howard Hughes Medical Institute
Warintra Pitsawong: Brandeis University and Howard Hughes Medical Institute
Marc Hömberger: Brandeis University and Howard Hughes Medical Institute
Sergey Ovchinnikov: Harvard University
Lucy Colwell: Google Research
Dorothee Kern: Brandeis University and Howard Hughes Medical Institute

Nature, 2024, vol. 625, issue 7996, 832-839

Abstract: Abstract AlphaFold2 (ref. 1) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein’s biological function often depends on multiple conformational substates2, and disease-causing point mutations often cause population changes within these substates3,4. We demonstrate that clustering a multiple-sequence alignment by sequence similarity enables AlphaFold2 to sample alternative states of known metamorphic proteins with high confidence. Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB5 and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic resonance spectroscopy to confirm an AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state compared with the more widely studied variant. To test AF-Cluster’s sensitivity to point mutations, we designed and experimentally verified a set of three mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternative states in protein families without known fold switching identified a putative alternative state for the oxidoreductase Mpt53 in Mycobacterium tuberculosis. Further development of such bioinformatic methods in tandem with experiments will probably have a considerable impact on predicting protein energy landscapes, essential for illuminating biological function.

Date: 2024
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DOI: 10.1038/s41586-023-06832-9

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