摘要

The fibrillation and deposition of amyloid-beta (A beta) peptides in human brains are pathologically linked to Alzheimer's disease (AD). Development of different inhibitors (peptides, organic molecules, and nanoparticles) to prevent A beta aggregation becomes a promising therapeutic strategy for AD treatment. We recently propose a "like-interacts-like'' design principle to computationally design/screen and experimentally validate a new set of hexapeptide inhibitors with completely different sequences from the A beta sequence. These hexapeptide inhibitors inhibit A beta aggregation and reduce A beta-induced cytotoxicity. However, inhibitory mechanisms of these hexapeptides and the underlying interactions between hexapeptides and A beta remain unclear. Herein we apply multi-scale computational methods (quantum-chemical calculations, molecular docking and explicit-solvent molecular dynamic simulation) to explore the structure, dynamics, and interaction between 3 identified hexapeptides (CTLWWG, GTVWWG, and CTIYWG) and different A beta-derived fragments and an A beta 17-42 pentamer. When interacting with 6 A beta-derived fragments, 3 hexapeptide inhibitors show stronger interactions with two lysine-included fragments ((16)KLVFFA(21) and (27)NKGAII(33)) than other fragments, indicating different sequence-specific interactions with A beta. When interacting with the A beta 17-42 pentamer, the 3 peptides show similar binding modes and interaction mechanisms by preferentially binding to the edge of the A beta 17-42 pentamer to potentially block the A beta elongation pathway. This work provides structural-based binding information on further modification and optimization of these peptide inhibitors to experimentally enhance their inhibitory abilities against A beta aggregation.