Genetic Selection of Peptide Inhibitors of Human Immunodeficiency Virus Type 1 Vpr
Bibliographic record
Abstract
Human immunodeficiency virus 1 (HIV-1) encodes a gene product, Vpr, that facilitates the nuclear uptake of the viral pre-integration complex in non-dividing cells and causes infected cells to arrest in the G(2) phase of the cell cycle. Vpr was also shown to cause mitochondrial dysfunction in human cells and budding yeasts, an effect that was proposed to lead to growth arrest and cell killing in budding yeasts and apoptosis in human cells. In this study, we used a genetic selection in Saccharomyces cerevisiae to identify hexameric peptides that suppress the growth arrest phenotype mediated by Vpr. Fifteen selected glutathione S-transferase (GST)-fused peptides were found to overcome to different extents Vpr-mediated growth arrest. Amino acid analysis of the inhibitory peptide sequences revealed the conservation of a di-tryptophan (diW) motif. DiW-containing GST-peptides interacted with Vpr in GST pull-down assays, and their level of interaction correlated with their ability to overcome Vpr-mediated growth arrest. Importantly, Vpr-binding GST-peptides were also found to alleviate Vpr-mediated apoptosis and G(2) arrest in HIV-1-producing CD4(+) T cell lines. Furthermore, they co-localized with Vpr and interfered with its nuclear translocation. Overall, this study defines a class of diW-containing peptides that inhibit HIV-1 Vpr biological activities most likely by interacting with Vpr and interfering with critical protein interactions.
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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 | 0.000 |
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".