Complex interplay between RAS GTPases and RASSF effectors regulates subcellular localization of YAP
Bibliographic record
Abstract
RAS GTPases bind effectors to convert upstream cues to changes in cellular function. Effectors of classical H/K/NRAS are defined by RBD/RA domains which recognize the GTP-bound conformation of these GTPases, yet the specificity of RBD/RAs for over 160 RAS superfamily proteins remains poorly explored. We have systematically mapped interactions between BRAF and four RASSF effectors, the largest family of RA-containing proteins, with all RAS, RHO and ARF small GTPases. 39 validated complexes reveal plasticity in RASSF binding, while BRAF demonstrates tight specificity for classical H/K/NRAS. Complex between RASSF5 and diverse RAS GTPases at the plasma membrane can activate Hippo signalling and sequester YAP in the cytosol. RASSF8 undergoes liquid-liquid phase separation and resides in YAP-associated membraneless condensates, which also engage several RAS and RHO GTPases. The poorly studied RASSF3 has been identified as a first potential effector of mitochondrial MIRO proteins, and its co-expression with these GTPases impacts mitochondria and peroxisome distribution. These data reveal the complex nature of GTPase-effector interactions and show their systematic elucidation can reveal completely novel and biologically relevant cellular processes.
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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 | 0.000 |
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".