Efficient Biochemical Method for Characterizing and Classifying Related Amyloidogenic Peptides

Abstract

Amyloidosis is a group of proteinopathies characterized by the systemic or organ-specific deposition of proteins in the form of amyloid fibers. Nearly 40 proteins play a role in these pathologies, and the structures of the associated fibers are beginning to be determined by Cryo-EM. However, the molecular events underlying the process, such as fiber nucleation and elongation, are poorly understood, which impairs developing efficient therapies. In most cases, only a few dozen amino acids of the pathological protein are found in the final structure of the fibers, while amyloid peptides comprising five to 10 amino acids are involved in the fiber nucleation process. The identification and biochemical characterization of these peptides are therefore of major scientific and clinical importance. We demonstrated that in silico approaches are limited due to the peptides’ small size and long-distance intra- and intermolecular interactions that occur during nucleation. To address this problem, we developed a novel biochemical method for characterizing and classifying batches of related peptides. Initial work to optimize our approach is based on the reference peptide PHF6 (β1) from Microtubule-Associated Protein Tau (MAPT) as compared to 22 related peptides. Depending on their biochemical properties and using the Garnier–Delamarche plot we propose, we classified these peptides into three groups: aggregative, amyloid, and soluble (neither aggregative nor amyloid). We emphasize that our biochemical classification method is applicable to any family of peptides and could be scaled up for high-throughput analyses.