The human orthologue of CdGAP is a phosphoprotein and a GTPase‐activating protein for Cdc42 and Rac1 but not RhoA
Bibliographic record
Abstract
BACKGROUND INFORMATION: Rho GTPases regulate a wide range of cellular functions affecting both cell proliferation and cytoskeletal dynamics. They cycle between inactive GDP- and active GTP-bound states. This cycle is tightly regulated by GEFs (guanine nucleotide-exchange factors) and GAPs (GTPase-activating proteins). Mouse CdGAP (mCdc42 GTPase-activating protein) has been previously identified and characterized as a specific GAP for Rac1 and Cdc42, but not for RhoA. It consists of an N-terminal RhoGAP domain and a C-terminal proline-rich region. In addition, CdGAP-related genes are present in both vertebrates and invertebrates. We have recently reported that two predominant isoforms of CdGAP (250 and 90 kDa) exist in specific mouse tissues. RESULTS: In the present study, we have identified and characterized human CdGAP (KIAA1204) which shares 76% sequence identity to the long isoform of mCdGAP (mCdGAP-l). Similar to mCdGAP, it is active in vitro and in vivo on both Cdc42 and Rac1, but not RhoA, and is phosphorylated in vivo on serine and threonine residues. In contrast with mCdGAP-l, human CdGAP interacts with ERK1/2 (extracellular-signal-regulated kinase 1/2) through a region that does not involve a DEF (docking site for ERK Phe-Xaa-Phe-Pro) domain. Also, the tissue distribution of CdGAP proteins appears to be different between human and mouse species. Interestingly, we found that CdGAP proteins cause membrane blebbing in COS-7 cells. CONCLUSIONS: Our results suggest that CdGAP properties are well conserved between human and mouse species, and that CdGAP may play an unexpected role in apoptosis.
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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) | 0.012 | 0.004 |
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".