Development of peptide-based amyloid inhibitors to specifically and efficiently inhibit amyloid aggregation is very critical for (pre)clinical treatment of neurodegenerative diseases. But, all of existing peptide-based amyloid inhibitors are mostly derived from their parent sequences, and the limited sequence diversity of these inhibitors significantly limits their inhibitory activity. It is highly desirable to explore other peptide-based inhibitors that are not directly derived from amyloid sequences. Here, we develop a hybrid high-throughput computational method to efficiently screen and design hexapeptide inhibitors against amyloid-β (Aβ) and hIAPP aggregation and toxicity from the first principle. Computationally screened/designed inhibitors are then validated for their inhibition activity using biophysical experiments. We propose and demonstrate a proof-of-concept of the “like-interacts-like” design principle that the self-assembling peptides are able to interact strongly with conformationally similar motifs of Aβ and hIAPP peptides and to competitively reduce amyloid-amyloid interactions, thus preventing amyloid aggregation and amyloid-induced toxicity. Such a <i>de novo</i> design could be generally applicable to design new peptide inhibitors against other amyloid diseases, beyond traditional peptide inhibitors with homologous sequences to parent amyloid peptides.<br/> <br/>

Molecular design of self-assembled β-sheet-forming peptides as amyloid inhibitors

251st National Meeting (2016)

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