Inhibition of Cellular HIV-1 Protease Activity by Lysyl-tRNA Synthetase
Bibliographic record
Abstract
During early assembly of human immunodeficiency virus type 1 (HIV-1), an assembly complex is formed, the components of which include genomic RNA, Gag, GagPol, tRNA(Lys), and lysyl tRNA synthetase (LysRS). Directly increasing or decreasing cellular expression of LysRS results in corresponding changes in viral infectivity and in the viral concentrations of LysRS, tRNA(Lys), and, surprisingly, reverse transcriptase (RT). Since altering the cellular expression of LysRS does not lead to a change in the incorporation of the RT precursor protein, GagPol, in protease-negative HIV-1, we propose that the altered viral content of RT resulting from alterations in cellular LysRS concentration results from the ability of LysRS to inhibit premature activation of Gag-Pol viral protease within the complex. Supporting this hypothesis, we find that increases and decreases in cellular LysRS expression are accompanied by 5-8-fold increases and 5-fold decreases, respectively, in the cytoplasmic proteolysis of Gag and GagPol to mature viral proteins. Using a novel bioluminescence resonance energy transfer assay to directly measure HIV-1 protease activity in vivo also indicates that the overexpression of LysRS in the cell reduces viral protease activity.
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".