The β-Subunit of the Signal Recognition Particle Receptor Is a Novel GTP-binding Protein without Intrinsic GTPase Activity
Bibliographic record
Abstract
The beta-subunit of the signal recognition particle receptor (SRbeta), a member of the Ras family of small molecular weight GTPases, is involved in the targeting of nascent polypeptide chains to the protein translocation machinery in the endoplasmic reticulum membrane. We purified SRbeta from an expressing strain of Escherichia coli and investigated the properties of the isolated GTPase. We find that, unlike other Ras family GTPases, most SRbeta purifies bound to GTP, and SRbeta-bound GTP is not easily exchanged with solution GTP. SRbeta possesses no detectable GTPase activity. Although a stable interaction between SRbeta and ribosomes is observed, SRbeta is not stimulated to hydrolyze GTP when incubated with ribosomes or ribosome-nascent chains. A GTPase mutant harboring a mutation in a region predicted to be functionally important, based on observations made in related GTPases, binds GTP with faster kinetics and appears to be a less stable protein but otherwise displays similar properties to the wild-type SRbeta GTPase. Our results demonstrate that as an isolated GTPase, SRbeta functions differently from the Arf- and Ras-type GTPases that it is most closely related to by sequence.
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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 | 0.001 |
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".