Mass Spectrometry and Machine Learning Reveal Determinants of Client Recognition by Antiamyloid Chaperones.

ABSTRACT: The assembly of proteins and peptides into amyloid fibrils is causally linked to serious disorders such as Alzheimer's disease. Multiple proteins have been shown to prevent amyloid formation in vitro and in vivo, ranging from highly specific chaperone-client pairs to completely nonspecific binding of aggregation-prone peptides. The underlying interactions remain elusive. Here, we turn to the machine learning-based structure prediction algorithm AlphaFold2 to obtain models for the nonspecific interactions of β-lactoglobulin, transthyretin, or thioredoxin 80 with the model amyloid peptide amyloid β and the highly specific complex between the BRICHOS chaperone domain of C-terminal region of lung surfactant protein C and its polyvaline target. Using a combination of native mass spectrometry (M

SUBMITTER: Osterlund N 

PROVIDER: S-EPMC9563204 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature