Interactions of Curcumin's Degradation Products with the Aβ42 Dimer: A Computational Study

Insights into the baicalein-induced destabilization of LS-shaped Aβ42 protofibrils using computer simulations

Amyloid-β (Aβ) peptides aggregate spontaneously into various aggregating species comprising oligomers, protofibrils, and mature fibrils in Alzheimer's disease (AD). Disrupting β-sheet rich neurotoxic smaller soluble Aβ42 oligomers formed at early stages is considered a potent strategy to interfere with AD pathology. Previous experiments have demonstrated the inhibition of the early stages of Aβ aggregation by baicalein; however, the molecular mechanism behind inhibition remains largely unknown. Thus, in this work, molecular dynamics (MD) simulations have been employed to illuminate the molecular mechanism of baicalein-induced destabilization of preformed Aβ42 protofibrils. Baicalein binds to chain A of the Aβ42 protofibril through hydrogen bonds, π-π interactions, and hydrophobic contacts with the central hydrophobic core (CHC) residues of the Aβ42 protofibril. The binding of baicalein to the CHC region of the Aβ42 protofibril resulted in the elongation of the kink angle and disruption of K28-A42 salt bridges, which resulted in the distortion of the protofibril structure. Importantly, the β-sheet content was notably reduced in Aβ42 protofibrils upon incorporation of baicalein with a concomitant increase in the coil content, which is consistent with ThT fluorescence and AFM images depicting disaggregation of pre-existing Aβ42 fibrils on the incorporation of baicalein. Remarkably, the interchain binding affinity in Aβ42 protofibrils was notably reduced in the presence of baicalein leading to distortion in the overall structure, which agrees with the structural stability analyses and conformational snapshots. This work sheds light on the molecular mechanism of baicalein in disrupting the Aβ42 protofibril structure, which will be beneficial to the design of therapeutic candidates against disrupting β-sheet rich neurotoxic Aβ42 oligomers in AD.

Curcumin-derived carbon quantum dots: Dual actions in mitigating tau hyperphosphorylation and amyloid beta aggregation

The amyloid cascade and tau hypotheses both hold significant implications for the pathogenesis of Alzheimer's disease (AD). Curcumin shows potential by inhibiting the aggregation of amyloid beta (Aβ) and reducing tau hyperphosphorylation, however, its use is limited due to issues with solubility and bioavailability. Carbon dots, recognized for their high biocompatibility and optimal water solubility, have demonstrated the capability to inhibit either Aβ or tau aggregation. Nonetheless, their effects on tau hyperphosphorylation are yet to be extensively explored. This study aims to evaluate the water-soluble curcumin-derived carbon quantum dots (Cur-CQDs) synthesized via an eco-friendly method, designed to preserve the beneficial effects of curcumin while overcoming solubility challenges. The synthesis of Cur-CQDs involves a single-step dry heating process using curcumin, resulting in dots that exhibit negligible cytotoxicity to SH-SY5Y cells at the examined concentrations. Notably, Cur-CQDs have shown the ability to simultaneously mitigate Aβ aggregation and tau hyperphosphorylation. Therefore, it is suggested that Cur-CQDs may hold potential for AD treatment, a hypothesis deserving of further research.

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

Identification of Catechins' Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ₄₂. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ₄₂. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.