Mapping the Gα13 Binding Interface of the rgRGS Domain of p115RhoGEF
Bibliographic record
Abstract
Structural requirements for function of the Rho GEF (guanine nucleotide exchange factor) regulator of G protein signaling (rgRGS) domains of p115RhoGEF and homologous exchange factors differ from those of the classical RGS domains. An extensive mutagenesis analysis of the p115RhoGEF rgRGS domain was undertaken to determine its functional interface with the Galpha(13) subunit. Results indicate that there is global resemblance between the interaction surface of the rgRGS domain with Galpha(13) and the interactions of RGS4 and RGS9 with their Galpha substrates. However, there are distinct differences in the distribution of functionally critical residues between these structurally similar surfaces and an additional essential requirement for a cluster of negatively charged residues at the N terminus of rgRGS. Lack of sequence conservation within the N terminus may also explain the lack of GTPase-activating protein (GAP) activity in a subset of the rgRGS domains. For all mutations, loss of functional GAP activity is paralleled by decreases in binding to Galpha(13). The same mutations, when placed in the context of the p115RhoGEF molecule, produce deficiencies in GAP activity as observed with the rgRGS domain alone but show no attenuation of the regulation of Rho exchange activity by Galpha(13). This suggests that the rgRGS domain may serve a structural or allosteric role in the regulation of the nucleotide exchange activity of p115RhoGEF on Rho by Galpha(13).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".