Elucidating the Interaction Dynamics Between a Novel Terpolymer and Aβ42: Unlocking Therapeutic Potential for Alzheimer's Disease
Bibliographic record
Abstract
Abstract Background Alzheimer's disease (AD), a progressive neurodegenerative disorder, is closely associated with the aggregation of amyloid‐beta (Aβ) peptides, particularly Aβ42. Toxic oligomeric forms of Aβ42 are implicated in synaptic dysfunction and cognitive decline, making them a key target for therapeutic interventions 1 . This study explores the interactions between a novel biodegradable terpolymer we developed for delivering imaging and therapeutic agents to the AD brain 2,3 and Aβ42 to evaluate its therapeutic potential. Method The biding affinity between Aβ42 and the terpolymer was evaluated using biolayer interferometry (BLI). Replica exchange molecular dynamics (REMD) 4 simulation was performed to analyze conformational changes in Aβ42 upon binding to the terpolymer. Circular dichroism (CD) spectroscopy, transmission electron microscopy (TEM), and confocal microscopy were employed to monitor time course of structural transitions, aggregation patterns, and cellular interactions. SH‐SY5Y cells were used to assess the effect of the terpolymer on attenuating Aβ42‐induced cytotoxicity. Result REMD simulations revealed rapid conformational transitions in Aβ42 upon terpolymer binding, shifting from random coil and α‐helical structures to stabilized β‐sheet‐rich states. CD spectroscopy demonstrated accelerated secondary structure transitions, corroborating the simulation findings. TEM showed that the terpolymer disrupted conventional Aβ42 aggregation patterns, resulting in smaller, irregular aggregates rather than typical long fibrils. Cellular assays indicated that the terpolymer significantly reduced Aβ42‐induced cytotoxicity, improving cell viability in the terpolymer treated groups. Confocal microscopy revealed cellular uptake of Aβ42‐terpolymer complexes, reducing extracellular toxicity and harmful interactions with cellular membranes. Conclusion This study highlights the capability of the terpolymer in modulating Aβ42 aggregation dynamics, mitigating toxic oligomer formation and alleviating its neurotoxic effects. These findings present a promising approach for developing polymer‐based therapies targeting Alzheimer's disease, offering a novel pathway to combat neurodegeneration. References Okumura, H., J Phys Chem B 2023, 127 (51), 10931‐10940. Park E, et al. Advanced Science. 2023, 10(12):2207238. Li, L.Y.; Park, E. et al. Nanotoxicology 2024 , 1‐20. Li, L.Y.; Park, E. et al. Nanotoxicology 2024, 1‐20.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".