The prolyl isomerase, FKBP25, interacts with RNA-engaged nucleolin and the pre-60S ribosomal subunit
Bibliographic record
Abstract
Peptidyl-proline isomerases of the FK506-binding protein (FKBP) family belong to a class of enzymes that catalyze the cis-trans isomerization of prolyl-peptide bonds in proteins. A handful of FKBPs are found in the nucleus, implying that the isomerization of proline in nuclear proteins is enzymatically controlled. FKBP25 is a nuclear protein that has been shown to associate with chromatin modifiers and transcription factors. In this study, we performed the first proteomic characterization of FKBP25 and found that it interacts with numerous ribosomal proteins, ribosomal processing factors, and a small selection of chromatin modifiers. In agreement with previous reports, we found that nucleolin is a major FKBP25-interacting protein and demonstrated that this interaction is dependent on rRNA. FKBP25 interacts with the immature large ribosomal subunit in nuclear extract but does not associate with mature ribosomes, implicating this FKBP's action in ribosome biogenesis. Despite engaging nascent 60S ribosomes, FKBP25 does not affect steady-state levels of rRNAs or its pre-rRNA intermediates. We conclude that FKBP25 is likely recruited to preribosomes to chaperone one of the protein components of the ribosome large subunit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".