Mass spectrometric data for chaperone-ligand interactions

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 non-specific binding of
aggregation-prone peptides. The underlying interactions remain elusive.
Here, we turn to the machine learning-based structure prediction algorithm
AlphaFold2 (AF2) to obtain models for the non-specific interactions
of b-lactoglobulin (bLG), transthyretin (TTR), or Thioredoxin 80
(T80) with the model amyloid peptide Amyloid b (Ab), and
the highly specific complex between the BRICHOS chaperone domain of lung
surfactant protein C (CTC) and its polyvaline target. Using a combination
of native mass spectrometry (MS) and ion mobility MS, we show that
non-specific chaperoning is driven predominantly by hydrophobic
interactions of Ab with hydrophobic surfaces in bLG,
TTR, and T80, and in part regulated by oligomer stability. For CTC, native
MS and hydrogen-deuterium exchange MS reveal that a disordered region
recognizes the polyvaline target by forming a
complementary b-strand. Hence, we show that AF2 and MS can yield
atomistic models of hard-to-capture protein interactions that reveal
different chaperoning mechanisms based on separate ligand properties and
may provide possible clues for specific therapeutic intervention.