RASSF effectors couple diverse RAS subfamily GTPases to the Hippo pathway
Bibliographic record
Abstract
Small guanosine triphosphatases (GTPases) of the RAS superfamily signal by directly binding to multiple downstream effector proteins. Effectors are defined by a folded RAS-association (RA) domain that binds exclusively to GTP-loaded (activated) RAS, but the binding specificities of most RA domains toward more than 160 RAS superfamily GTPases have not been characterized. Ten RA domain family (RASSF) proteins comprise the largest group of related effectors and are proposed to couple RAS to the proapoptotic Hippo pathway. Here, we showed that RASSF1-6 formed complexes with the Hippo kinase ortholog MST1, whereas RASSF7-10 formed oligomers with the p53-regulating effectors ASPP1 and ASPP2. Moreover, only RASSF5 bound directly to activated HRAS and KRAS, and RASSFs did not augment apoptotic induction downstream of RAS oncoproteins. Structural modeling revealed that expansion of the RASSF effector family in vertebrates included amino acid substitutions to key residues that direct GTPase-binding specificity. We demonstrated that the tumor suppressor RASSF1A formed complexes with the RAS-related GTPases GEM, REM1, REM2, and the enigmatic RASL12. Furthermore, interactions between RASSFs and RAS GTPases blocked YAP1 nuclear localization. Thus, these simple scaffolds link the activation of diverse RAS family small G proteins to Hippo or p53 regulation.
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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".