State-selective inhibition of alpha-synuclein aggregation by de novo oligomer-binding proteins
TL;DR
Deep learning-based protein design is used to generate de novo binders capturing this region of α-synuclein in a β-strand conformation to establish a set of molecules that target distinct aggregation intermediates and mechanistically reshape αSyn assembly.
Abstract
The intrinsically disordered, non-amyloid-β component domain of α-synuclein (αSyn) drives aggregation in Parkinson’s disease but lacks a stable epitope for structure-based drug design. We used deep learning-based protein design to generate de novo binders capturing this region in a β-strand conformation. Three designs bound αSyn with nanomolar affinities, with solution NMR spectroscopy supporting the intended fold. All three suppressed fibril formation at substoichiometric ratios, and fitting of aggregation kinetics resolved the microscopic steps inhibited by each. Notably, one binder preferentially engaged oligomers and inhibited secondary nucleation, both closely linked to toxicity. In cells, all three suppressed seeded αSyn assembly, with the oligomer binder being the most effective. Together, these findings establish a set of molecules that target distinct aggregation intermediates and mechanistically reshape αSyn assembly.
