Positively Charged Chitosan and <i>N</i>-Trimethyl Chitosan Inhibit Aβ40 Fibrillogenesis
Bibliographic record
Abstract
Amyloid fibrils, formed by aggregation of improperly folded or intrinsically disordered proteins, are closely related with the pathology of a wide range of neurodegenerative diseases. Hence, there is a great deal of interest in developing molecules that can bind and inhibit amyloid formation. In this regard, we have investigated the effect of two positively charged polysaccharides, chitosan (CHT) and its quarternary derivative N-trimethyl chitosan chloride (TMC), on the aggregation of Aβ40 peptide. Our aggregation kinetics and atomic force microscopy (AFM) studies show that both CHT and TMC exhibit a concentration-dependent inhibiting activity on Aβ40 fibrillogenesis. Systematic pH-dependent studies demonstrate that the attractive electrostatic interactions between the positively charged moieties in CHT/TMC and the negatively charged residues in Aβ40 play a key role in this inhibiting activity. The stronger inhibiting activity of TMC than CHT further suggests the importance of charge density of the polymer chain in interacting with Aβ40 and blocking the fibril formation. The possible interactions between CHT/TMC and Aβ40 are also revealed at the atomic level by molecular docking simulation, showing that the Aβ40 monomer could be primarily stabilized by electrostatic interactions with charged amines of CHT and quaternary amines of TMC, respectively. Binding of CHT/TMC on the central hydrophobic core region of Aβ40 peptide may be responsible for blocking the propagation of the nucleus to form fibrillar structures. These results suggest that incorporation of sugar units such as d-glucosamine and N-trimethyl-d-glucosamine into polymer structural template may serve as a new strategy for designing novel antiamyloid molecules.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".