Role of RNA in Facilitating Gag/Gag-Pol Interaction
Bibliographic record
Abstract
We have examined the influence of RNA upon the interaction of Gag-Pol with Gag during human immunodeficiency virus type 1 (HIV-1) assembly. COS7 cells were transfected with protease-negative HIV-1 proviral DNA, and Gag/Gag-Pol complexes were detected by coimmunoprecipitation with anti-integrase. In COS7 cells, Gag/Gag-Pol is found almost entirely in pelletable, membrane-bound complexes. Exposure of cells to 1% Triton X-100 releases Gag/Gag-Pol from bulk membrane, but the complexes remain pelletable. The role of RNA in facilitating the interaction between Gag and Gag-Pol was examined in these bulk membrane-free, pelletable complexes. The specific presence of viral genomic RNA is not required to maintain the Gag/Gag-Pol interaction, but some type of RNA is, since exposure to RNase destabilized the Gag/Gag-Pol complex. When present only in Gag, the nucleocapsid mutation R7R10K11S, which inhibits Gag binding to RNA, inhibits the formation of both Gag and Gag/Gag-Pol complexes. When present only in Gag-Pol, this mutation has no effect upon complex formation. This result indicates that Gag-Pol may not interact directly with RNA but rather requires RNA-facilitated Gag multimerization for its interaction with Gag.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".