All-Atom Stability and Oligomerization Simulations of Polyglutamine Nanotubes with and without the 17-Amino-Acid N-Terminal Fragment of the Huntingtin Protein
Bibliographic record
Abstract
Several neurodegenerative diseases are associated with the polyglutamine (polyQ) repeat disorder in which a segment of consecutive glutamines in the native protein is produced with too many glutamines. Huntington's disease, for example, is related to the misfolding of the Huntingtin protein which occurs when the polyQ segment has more than approximately 36 glutamines. Experimentally, it is known that the polyQ segment alone aggregates into β-rich conformations such as amyloid fibrils. Its aggregation is modulated by the number of glutamine residues as well as by the surrounding amino acid sequences such as the 17-amino-acid N-terminal fragment of Huntingtin which increases the aggregation rate. Little structural information is available, however, regarding the first steps of aggregation and the atomistic mechanisms of oligomerization are yet to be described. Following previous coarse-grained replica-exchange molecular dynamics simulations that show the spontaneous formation of a nanotube consisting of two intertwined antiparallel strands (Laghaei, R.; Mousseau, N. J. Chem. Phys. 2010, 132, 165102), we study this configuration and some extensions of it using all-atom explicit solvent MD simulations. We compare two different lengths for the polyQ segment, 40 and 30 glutamines, and we investigate the impact of the Huntingtin N-terminal residues (htt(NT)). Our results show that the dimeric nanotubes can provide a building block for the formation of longer nanotubes (hexamers and octamers). These longer nanotubes are characterized by large β-sheet propensities and a small solvent exposure of the main-chain atoms. Moreover, the oligomerization between two nanotubes occurs through the formation of protein/protein H-bonds and can result in an elongation of the water-filled core. Our results also show that the htt(NT) enhances the structural stability of the β-rich seeds, suggesting a new mechanism by which it can increase the aggregation rate of the amyloidogenic polyQ sequence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".