Dual recognition of the ribosome and the signal recognition particle by the SRP receptor during protein targeting to the endoplasmic reticulum
Bibliographic record
Abstract
We have analyzed the interactions between the signal recognition particle (SRP), the SRP receptor (SR), and the ribosome using GTPase assays, biosensor experiments, and ribosome binding assays. Possible mechanisms that could contribute to an enhanced affinity between the SR and the SRP-ribosome nascent chain complex to promote protein translocation under physiological ionic strength conditions have been explored. Ribosomes or 60S large ribosomal subunits activate the GTPase cycle of SRP54 and SRalpha by providing a platform for assembly of the SRP-SR complex. Biosensor experiments revealed high-affinity, saturable binding of ribosomes or large ribosomal subunits to the SR. Remarkably, the SR has a 100-fold higher affinity for the ribosome than for SRP. Proteoliposomes that contain the SR bind nontranslating ribosomes with an affinity comparable to that shown by the Sec61 complex. An NH2-terminal 319-residue segment of SRalpha is necessary and sufficient for binding of SR to the ribosome. We propose that the ribosome-SR interaction accelerates targeting of the ribosome nascent chain complex to the RER, while the SRP-SR interaction is crucial for maintaining the fidelity of the targeting reaction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".