Mutations in conserved regions 1, 2, and 3 of Raf‐1 that activate transforming activity
Bibliographic record
Abstract
To investigate the role of Raf-1 in v-Ha-ras transformation, we have isolated and characterized a number of Raf-1 mutants that display increased transforming activity in Rat2 fibroblasts. A dipeptide deletion (Delta144-145) in the cysteine-rich domain (CRD) of conserved region (CR) 1 increased the interaction between Raf-1 and v-Ha-ras effector loop mutants in the yeast two-hybrid system, supporting the proposal that the CRD serves as a secondary ras-binding domain. Many activating mutations were located in CR2. Two representative CR2 mutants (Delta250-258 and S257L) displayed increased interaction with v-Ha-ras effector loop mutants and with mitogen-activated protein kinase/extracellular signal-regulated kinase (ERK) kinase (MEK) 1 in the two-hybrid system. One novel mutation in CR3 was recovered; G361S affected the third glycine of the GXGXXG protein kinase motif involved in ATP binding. Expression of G361S Raf-1 in Rat2 fibroblasts activated MEK and ERK. The CR1, CR2, and CR3 activating mutations, when combined in cis, cooperated in transforming Rat2 fibroblasts. Conversely, Raf-1 transforming activity was decreased when the S257L or G361S mutation was combined in cis with the R89E substitution, which disrupts ras-Raf interaction. This mutant analysis provides additional information about the distinct functions of individual Raf-1 regions and documents a novel genetic mechanism for activating an oncogenic kinase.
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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) | 0.001 | 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".