Identification of the fibril-forming peptide sequences is biologically important for understanding the sequence-structure-activity relationship of amyloid diseases and for finding potential inhibitors and therapeutic strategies against amyloid diseases. Here, we marry QSAR model, molecular dynamics (MD) simulations, and biophysical experiments to search for hexapeptide sequences with high tendency to form amyloid-like fibrils. We first use existing amyloid sequences to develop a QSAR model which predicts amyloid-forming sequences from a complete hexapeptide library. The preselected sequences from the QSAR model are examined their ability whether or not to form �-sheet structures using MD simulations. Ten computationally screened and designed sequences are further experimentally validated for their ability to form �-sheet-rich fibrils using AFM, CD, FTIR, and X-ray. These self-assembly hexapeptides could serve as potential inhibitors to interfere with naturally-occurring amyloid peptide self-assembly and thus to prevent amyloid fibril formation.

Identification of peptide sequences to form amyloid-like fibrils

243rd National Meeting (2012)

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