Modeling of chemical inhibition from amyloid protein aggregation kinetics

Modulation of α-Synuclein Aggregation In Vitro by a DNA Aptamer

Protein aggregation is an important problem for human health and biotechnology, with consequences in areas ranging from neurodegenerative diseases to protein production yields. Methods to modulate protein aggregation are therefore essential. One suggested method to modulate protein aggregation is the use of nucleic acid aptamers, that is, single-stranded nucleic acids that have been selected to specifically bind to a target. Previous studies in some systems have demonstrated that aptamers may inhibit protein aggregation, including for α-synuclein, a protein implicated in synucleinopathies. However, the mechanisms by which aptamers might affect or modulate aggregation have not been fully determined. In this study, we investigated the effect of an aptamer that binds α-synuclein oligomer, T-SO508, on α-synuclein aggregation in vitro using thioflavin T to monitor aggregation kinetics, and we performed atomic force microscopy, transmission electron microscopy, and analytical ultracentrifugation to characterize intermediate structures. The results indicated that T-SO508, but not control DNA sequences, extends the lag phase of aggregation and stabilizes formation of a small non-fibrillar aggregate complex. Attempts to use the aptamer-induced complexes to seed fibril formation did not in fact accelerate aggregation, indicating that these structures are off-pathway for aggregation. This study highlights a potential mechanism by which aptamers may modulate the aggregation properties of proteins.

Modeling the Inhibition Kinetics of Curcumin, Orange G, and Resveratrol with Amyloid-β Peptide

The β-amyloid (Aβ) protein aggregation into toxic forms is one of the major factors in the Alzheimer's disease (AD) pathology. Screening compound libraries as inhibitors of Aβ-aggregation is a common strategy to discover novel molecules as potential therapeutics in AD. In this regard, thioflavin T (ThT)-based fluorescence spectroscopy is a widely used in vitro method to identify inhibitors of Aβ aggregation. However, conventional data processing of the ThT assay experimental results generally provides only qualitative output and lacks inhibitor-specific quantitative data, which can offer a number of advantages such as identification of critical inhibitor-specific parameters required to design superior inhibitors and reduce the need to conduct extensive in vitro kinetic studies. Therefore, we carried out mathematical modeling based on logistic equation and power law (PL) model to correlate the experimental results obtained from the ThT-based Aβ40 aggregation kinetics for small-molecule inhibitors curcumin, orange G, and resveratrol and quantitatively fit the data in a logistic equation. This approach provides important inhibitor-specific parameters such as lag time λ, inflection point τ, maximum slope v _m, and apparent rate constant k _app, which are particularly useful in comparing the effectiveness of potential Aβ40 aggregation inhibitors and can be applied in drug discovery campaigns to compare and contrast Aβ40 inhibition data for large compound libraries.

Biophysical and in Vivo Studies Identify a New Natural-Based Polyphenol, Counteracting Aβ Oligomerization in Vitro and Aβ Oligomer-Mediated Memory Impairment and Neuroinflammation in an Acute Mouse Model of Alzheimer's Disease

In this study natural-based complex polyphenols, obtained through a smart synthetic approach, have been evaluated for their ability to inhibit the formation of Aβ₄₂ oligomers, the most toxic species causing synaptic dysfunction, neuroinflammation, and neuronal death leading to the onset and progression of Alzheimer's disease. In vitro neurotoxicity tests on primary hippocampal neurons have been employed to select nontoxic candidates. Solution NMR and molecular docking studies have been performed to clarify the interaction mechanism of Aβ₄₂ with the synthesized polyphenol derivatives, and highlight the sterical and chemical requirements important for their antiaggregating activity. NMR results indicated that the selected polyphenolic compounds target Aβ₄₂ oligomeric species. Combined NMR and docking studies indicated that the Aβ₄₂ central hydrophobic core, namely, the 17-31 region, is the main interaction site. The length of the peptidomimetic scaffold and the presence of a guaiacol moiety were identified as important requirements for the antiaggregating activity. In vivo experiments on an Aβ₄₂ oligomer-induced acute mouse model highlighted that the most promising polyphenolic derivative (PP04) inhibits detrimental effects of Aβ₄₂ oligomers on memory and glial cell activation. NMR kinetic studies showed that PP04 is endowed with the chemical features of true inhibitors, strongly affecting both the Aβ₄₂ nucleation and growth rates, thus representing a promising candidate to be further developed into an effective drug against neurodegenerative diseases of the amyloid type.

High-Throughput Screening Methodology to Identify Alpha-Synuclein Aggregation Inhibitors

An increasing number of neurodegenerative diseases are being found to be associated with the abnormal accumulation of aggregated proteins in the brain. In Parkinson's disease, this process involves the aggregation of alpha-synuclein (α-syn) into intraneuronal inclusions. Thus, compounds that inhibit α-syn aggregation represent a promising therapeutic strategy as disease-modifying agents for neurodegeneration. The formation of α-syn amyloid aggregates can be reproduced in vitro by incubation of the recombinant protein. However, the in vitro aggregation of α-syn is exceedingly slow and highly irreproducible, therefore precluding fast high throughput anti-aggregation drug screening. Here, we present a simple and easy-to-implement in-plate method for screening large chemical libraries in the search for α-syn aggregation modulators. It allows us to monitor aggregation kinetics with high reproducibility, while being faster and requiring lower protein amounts than conventional aggregation assays. We illustrate how the approach enables the identification of strong aggregation inhibitors in a library of more than 14,000 compounds.

The Impact of Mathematical Modeling in Understanding the Mechanisms Underlying Neurodegeneration: Evolving Dimensions and Future Directions

Neurodegenerative diseases are a heterogeneous group of disorders that are characterized by the progressive dysfunction and loss of neurons. Here, we distil and discuss the current state of modeling in the area of neurodegeneration, and objectively compare the gaps between existing clinical knowledge and the mechanistic understanding of the major pathological processes implicated in neurodegenerative disorders. We also discuss new directions in the field of neurodegeneration that hold potential for furthering therapeutic interventions and strategies.