Predicting multiple conformations via sequence clustering and AlphaFold2.

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 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 KaiB⁵ and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic re

SUBMITTER: Wayment-Steele HK 

PROVIDER: S-EPMC10808063 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature