Proteomic Characterization of Protein Phosphatase Complexes of the Mammalian Nucleus
Bibliographic record
Abstract
Our knowledge of the serine/threonine protein phosphatases of the mammalian nucleus is limited compared with their cytosolic counterparts. Microcystin-Sepharose chromatography and mass spectrometry were utilized to affinity purify and identify protein phosphatase-associated proteins from isolated rat liver nuclei. Far Western analysis with labeled protein phosphatase 1 (PP1) showed that many more PP1 binding proteins exist in the nucleus than were previously demonstrated. Mass spectrometry confirmed the presence in the nucleus of the mammalian PP1 isoforms alpha1, alpha2, beta, and gamma1, plus the Aalpha and several of the B and B' subunits that are complexed to PP2A. Other proteins enriched on the microcystin matrix include the spliceosomal proteins known as the U2 snRNPs SAP145 and SAP155 and the U5 snRNPs p116 and p200, myosin heavy chain, and a nuclear PP1 myosin-targeting subunit related to M110. The putative RNA binding protein ZAP was also established as a nuclear PP1 binding protein using the criteria of co-purification with PP1 on microcystin-Sepharose, co-immunoprecipation, binding PP1 in an overlay assay, and presence of a putative PP1 binding site (KKRVRWAD). These results further support a key role for protein phosphatases in several nuclear functions, including the regulation of pre-mRNA splicing.
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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 | 0.001 |
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".