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. 2018 May 31;23(6):1320.
doi: 10.3390/molecules23061320.

Computational Insight into the Effect of Natural Compounds on the Destabilization of Preformed Amyloid-β(1⁻40) Fibrils

Affiliations

Computational Insight into the Effect of Natural Compounds on the Destabilization of Preformed Amyloid-β(1⁻40) Fibrils

Francesco Tavanti et al. Molecules. .

Abstract

One of the principal hallmarks of Alzheimer's disease (AD) is related to the aggregation of amyloid-β fibrils in an insoluble form in the brain, also known as amyloidosis. Therefore, a prominent therapeutic strategy against AD consists of either blocking the amyloid aggregation and/or destroying the already formed aggregates. Natural products have shown significant therapeutic potential as amyloid inhibitors from in vitro studies as well as in vivo animal tests. In this study, the interaction of five natural biophenols (curcumin, dopamine, (-)-epigallocatechin-3-gallate, quercetin, and rosmarinic acid) with amyloid-β(1⁻40) fibrils has been studied through computational simulations. The results allowed the identification and characterization of the different binding modalities of each compounds and their consequences on fibril dynamics and aggregation. It emerges that the lateral aggregation of the fibrils is strongly influenced by the intercalation of the ligands, which modulates the double-layered structure stability.

Keywords: Alzheimer’s disease; amyloid fibrils; biophenols; ligand–protofiber interactions; molecular dynamics simulation; natural compounds.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Cartoon representation of double-layered structures of Aβ(1–40) oligomers facing through their β-1, in (a), and β-2 β-sheets, in (b). Fibrils are colored according to their secondary structures. Amino acids at the interface are explicitly represented (color code: blue for positively charged, red for negatively charged, and white for hydrophobic amino acid residues). Black arrows roughly represent the intersheet distance.
Figure 2
Figure 2
Pulling directions applied to protofibril (2) during the calculation of the forces needed for double-layered destruction: along the x-axis (i.e., outward shift of the protofibril (2) along its secondary axes), the y-axis (i.e., lateral shift of the protofibril (2) along its primary axes), and the z-axis (i.e., vertical shift, progressive removal of protofibril (2)).
Figure 3
Figure 3
Ball-and-stick representation of the ligand binding sites obtained by REMD. Amino acids (single-letter code) involved in the interactions are reported for each binding site with different colors: Amino acids belonging to the N-terminal site are in blue, to the the β-1 site in cyan, to the Elbow site in orange, to the β-2 site in red, to the C-terminal site in purple, and to the Over site in black).
Figure 4
Figure 4
Probability of occupancy of each binding site (a) and binding free energy (b) for each ligand considered.
Figure 5
Figure 5
(a) Time evolution of the Aβ(1–40) secondary structure (computed with the GROMACS DSSP tool) upon EGCG binding on the β-2 β-sheet groove. The perturbation induced at the monomers lying at the head of the protofibril is highlighted by a black box. For clarity’s sake, only the top three Aβ(1–40) monomers are shown. (b) Conformation of F19 and L34 before (left) and after (right) the interaction of EGCG with M35.

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