Login / Signup

Computational Study of the Aza-Michael Addition of the Flavonoid (+)-Taxifolin in the Inhibition of β-Amyloid Fibril Aggregation.

Tiziana GinexMarta TriusFrancisco Javier Luque
Published in: Chemistry (Weinheim an der Bergstrasse, Germany) (2018)
Inhibition of abnormal protein self-aggregation is an attractive strategy against amyloidogenic diseases, but has found limited success due to the complexity of protein self-assembly, the absence of fully reproducible aggregation assays, and the scarce knowledge of the inhibition mechanisms by small molecules. In this context, catechol-containing compounds may lead to covalent adducts with amyloid fibrils that interfere with the aggregation process. In particular, the covalent adduct formed between the oxidized form of (+)-taxifolin and an β-amyloid (Aβ42) suggests the involvement of a specific recognition motif that enables the chemical reaction with Aβ42. In this study, we have examined the mechanisms implicated in the aza-Michael addition of the o-quinone species of (+)-taxifolin with Aβ42 fibrils. The results support the binding of (+)-taxifolin to the hydrophobic groove delimited by the edges defined by Lys16 and Glu22 residues in the fibril. The chemical reaction proceeds through the nucleophilic attack of the deprotonated amino group of a Lys16 residue in a process activated by the interaction between the o-quinone ring with a vicinal Lys16 residue, as well as by a water-assisted proton transfer, which is the rate-limiting step of the reaction. This specific inhibition mechanism, which may explain the enhanced anti-aggregating activity of oxidized flavonoids compared to fresh compounds, holds promise for developing disease-modifying therapies.
Keyphrases
  • healthcare
  • binding protein
  • protein protein
  • high throughput
  • big data
  • small molecule
  • machine learning
  • artificial intelligence