Incorporation of Radiolabeled Prenyl Alcohols and Their Analogs into Mammalian Cell Proteins: A Useful Tool for Studying Protein Prenylation
Bibliographic record
Abstract
Prenylated proteins comprise a diverse family of proteins that are posttranslationally modified by either a farnesyl group or one or more geranylgeranyl groups ( 1 - 3 ). Recent studies suggest that members of this family are involved in a number of cellular processes, including cell signaling ( 4 - 6 ), differentiation ( 7 - 9 ), proliferation ( 10 - 12 ), cytoskeletal dynamics ( 13 - 15 ), and endocytic and exocytic transport ( 4 , 16 , 17 ). The authors’ studies have focused on the role of prenylated proteins in the cell cycle ( 18 ). Exposure of cultured cells to competitive inhibitors (statins) of 3-hydroxy-3-methylglutaryl Coenzyme A (HMG-CoA) reductase not only blocks the biosynthesis of mevalonic acid (MVA), the biosynthetic precursor of both farnesyl and geranylgeranyl groups, but pleiotropically inhibits DNA replication and cell-cycle progression ( 10 , 18 - 20 ). Both phenomena can be prevented by the addition of exogenous MVA ( 10 , 18 , 19 ). The authors have observed that all- trans -geranylgeraniol (GGOH) and, in a few cases, all- trans -farnesol (FOH) can prevent the statin-induced inhibition of DNA synthesis ( 21 ). In an effort to understand the biochemical basis of these effects, the authors have developed methods for the labeling and two-dimensional gel analysis of prenylated proteins that should be widely applicable. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".