Atomistic mechanisms of huntingtin N‐terminal fragment insertion on a phospholipid bilayer revealed by molecular dynamics simulations
Bibliographic record
Abstract
The huntingtin protein is characterized by a segment of consecutive glutamines (Q(N)) that is responsible for its fibrillation. As with other amyloid proteins, misfolding of huntingtin is related to Huntington's disease through pathways that can involve interactions with phospholipid membranes. Experimental results suggest that the N-terminal 17-amino-acid sequence (htt(NT)) positioned just before the Q(N) region is important for the binding of huntingtin to membranes. Through all-atom explicit solvent molecular dynamics simulations, we unveil the structure and dynamics of the htt(NT)Q(N) fragment on a phospholipid membrane at the atomic level. We observe that the insertion dynamics of this peptide can be described by four main steps-approach, reorganization, anchoring, and insertion-that are very diverse at the atomic level. On the membrane, the htt(NT) peptide forms a stable α-helix essentially parallel to the membrane with its nonpolar side-chains-mainly Leu-4, Leu-7, Phe-11 and Leu-14-positioned in the hydrophobic core of the membrane. Salt-bridges involving Glu-5, Glu-12, Lys-6, and Lys-15, as well as hydrogen bonds involving Thr-3 and Ser-13 with the phospholipids also stabilize the structure and orientation of the htt(NT) peptide. These observations do not significantly change upon adding the Q(N) region whose role is rather to provide, through its hydrogen bonds with the phospholipids' head group, a stable scaffold facilitating the partitioning of the htt(NT) region in the membrane. Moreover, by staying accessible to the solvent, the amyloidogenic Q(N) region could also play a key role for the oligomerization of htt(NT)Q(N) on phospholipid membranes.
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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 | 0.000 |
| 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".