Arginine methylation of the HIV-1 nucleocapsid protein results in its diminished function
Bibliographic record
Abstract
OBJECTIVE: The HIV-1 nucleocapsid protein (NC) is involved in transfer RNA3 annealing to the primer binding site of viral genomic RNA by means of two basic regions that are similar to the N-terminal portion of the arginine-rich motif (ARM) of Tat. As Tat is known to be asymmetrically arginine dimethylated by protein arginine methyltransferase 6 (PRMT6) in its ARM, we investigated whether NC could also act as a substrate for this enzyme. METHODS: Arginine methylation of NC was demonstrated in vitro and in vivo, and sites of methylation were determined by mutational analysis. The impact of the arginine methylation of NC was measured in RNA annealing and reverse transcription initiation assays. An arginine methyltransferase inhibitor (AMI)3.4 was tested for its effects on viral infectivity and replication in vivo. RESULTS: NC is a substrate for PRMT6 both in vitro and in vivo. NC possesses arginine dimethylation sites in each of its two basic regions at positions R10 and R32, and methylated NC was less able than wild-type to promote RNA annealing and participate in the initiation of reverse transcription. Exposure of HIV-1-infected MT2 and primary cord blood mononuclear cells to AMI3.4 led to increased viral replication, whereas viral infectivity was not significantly affected in multinuclear-activation galactosidase indicator assays. CONCLUSION: NC is an in-vivo target of PRMT6, and arginine methylation of NC reduces RNA annealing and the initiation of reverse transcription. These findings may lead to ways of driving HIV-infected cells out of latency with drugs that inhibit PRMT6.
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 | 0.001 |
| 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".