Predicting multiple conformations via sequence clustering and AlphaFold2.

Autor: Wayment-Steele HK; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA., Ojoawo A; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA., Otten R; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA.; Treeline Biosciences, Watertown, MA, USA., Apitz JM; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA., Pitsawong W; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA.; Biomolecular Discovery, Relay Therapeutics, Cambridge, MA, USA., Hömberger M; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA.; Treeline Biosciences, Watertown, MA, USA., Ovchinnikov S; Center for Systems Biology, Harvard University, Cambridge, MA, USA., Colwell L; Google Research, Cambridge, MA, USA.; Cambridge University, Cambridge, UK., Kern D; Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA. dkern@brandeis.edu.
Jazyk: angličtina
Zdroj: Nature [Nature] 2024 Jan; Vol. 625 (7996), pp. 832-839. Date of Electronic Publication: 2023 Nov 13.
DOI: 10.1038/s41586-023-06832-9
Abstrakt: 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 substates 2 , and disease-causing point mutations often cause population changes within these substates 3,4 . 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 KaiB 5 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.
(© 2023. The Author(s).)
Databáze: MEDLINE
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