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

Qi Tianyi, Fu Jingxuan, Wang Yajie, Zhao Ming, Zhang Zhaoxu, Peng Weicheng, Liu Qiqi, Liu Minghao, Li Shibai, Duan Qiannan, Wang Chunyu, Zhuang Jie, Yan Xiyun, Liu Yijin, Wang Hui, Huang Xinglu

Journal:Nature Nanotechnology

IF:37.5

DOI:10.1038/s41565-026-02225-x

PMID:

Published:2026-07-21

research field:

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, Aβ3 FTn Au , 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 Aβ3 FTn Au (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 Aβ3 FTn Au 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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