Computationally guided design of bioactive nanostructures for targeted clearance of amyloid-β aggregates in Alzheimer’s disease

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Abstract
Targeted clearance of pre-existing amyloid-β (Aβ) aggregation remains a central challenge in Alzheimer’s disease (AD) therapy. Here we report a computationally guided protein–gold hybrid nanostructure, Aβ3FTnAu, that integrates Aβ-recognition motifs into self-assembled human ferritin nanocages containing structurally defined gold nanoclusters composed of 12 gold atoms with Au–Au distances of 2.4–4.5 Å, enabling the selective recognition and disassembly of aggregated human Aβ. Structural analysis, mutagenesis and molecular simulations identify key interactions between gold-coordinating residues within Aβ3FTnAu (H118, T122, C130) and the Met35 residue of Aβ, revealing a mechanism in which multivalent engagement destabilizes fibrillar interfaces and promotes progressive plaque disassembly. In 5 × familial AD transgenic mice, systemic administration of Aβ3FTnAu reduced cerebral amyloid burden, preserved synaptic integrity and improved cognitive performance. This work establishes a rationally designed bioactive nanomaterial for targeted remodelling of pathological protein aggregates.

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