Karyopherins in nuclear pore biogenesis
Bibliographic record
Abstract
The mechanisms that govern the assembly of nuclear pore complexes (NPCs) remain largely unknown. Here, we have established a role for karyopherins in this process. We show that the yeast karyopherin Kap121p functions in the targeting and assembly of the nucleoporin Nup53p into NPCs by recognizing a nuclear localization signal (NLS) in Nup53p. This karyopherin-mediated function can also be performed by the Kap95p-Kap60p complex if the Kap121p-binding domain of Nup53p is replaced by a classical NLS, suggesting a more general role for karyopherins in NPC assembly. At the NPC, neighboring nucleoporins bind to two regions in Nup53p. One nucleoporin, Nup170p, associates with a region of Nup53p that overlaps with the Kap121p binding site and we show that they compete for binding to Nup53p. We propose that once targeted to the NPC, dissociation of the Kap121p-Nup53p complex is driven by the interaction of Nup53p with Nup170p. At the NPC, Nup53p exists in two separate complexes, one of which is capable of interacting with Kap121p and another that is bound to Nup170p. We propose that fluctuations between these two states drive the binding and release of Kap121p from Nup53p, thus facilitating Kap121p's movement through the NPC.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".