Identification of a Karyopherin β1/β2 Proline-Tyrosine Nuclear Localization Signal in Huntingtin Protein
Bibliographic record
Abstract
Among the known pathways of protein nuclear import, the karyopherin β2/transportin pathway is only the second to have a defined nuclear localization signal (NLS) consensus. Huntingtin, a 350-kDa protein, has defined roles in the nucleus, as well as a CRM1/exportin-dependent nuclear export signal; however, the NLS and exact pathway of import have remained elusive. Here, using a live cell assay and affinity chromatography, we show that huntingtin has a karyopherin β2-dependent proline-tyrosine (PY)-NLS in the amino terminus of the protein. This NLS comprises three consensus components: a basic charged sequence, a downstream conserved arginine, and a PY sequence. Unlike the classic PY-NLS, which has an unstructured intervening sequence between the consensus components, we show that a β sheet structured region separating the consensus elements is critical for huntingtin NLS function. The huntingtin PY-NLS is also capable of import through the importin/karyopherin β1 pathway but was not functional in all cell types tested. We propose that this huntingtin PY-NLS may comprise a new class of multiple import factor-dependent NLSs with an internal structural component that may regulate NLS activity.
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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".