In Vitro Identification and Characterization of an Early Complex Linking HIV-1 Genomic RNA Recognition and Pr55Gag Multimerization
Bibliographic record
Abstract
The minimal protein requirements that drive virus-like particle formation of human immunodeficiency virus type 1 (HIV-1) have been established. The C-terminal domain of capsid (CTD-CA) and nucleocapsid (NC) are the most important domains in a so-called minimal Gag protein (mGag). The CTD is essential for Gag oligomerization. NC is known to bind and encapsidate HIV-1 genomic RNA. The spacer peptide, SP1, located between CA and NC is important for the multimerization process, viral maturation and recognition of HIV-1 genomic RNA by NC. In this study, we show that NC in the context of an mGag protein binds HIV-1 genomic RNA with almost 10-fold higher affinity. The protein region encompassing the 11th alpha-helix of CA and the proposed alpha-helix in the CA/SP1 boundary region play important roles in this increased binding capacity. Furthermore, sequences downstream from stem loop 4 of the HIV-1 genomic RNA are also important for this RNA-protein interaction. In gel shift assays using purified mGag and a model RNA spanning the region from +223 to +506 of HIV-1 genomic RNA, we have identified an early complex (EC) formation between 2 proteins and 1 RNA molecule. This EC was not present in experiments performed with a mutant mGag protein, which contains a CTD dimerization mutation (M318A). These data suggest that the dimerization interface of the CTD plays an important role in EC formation, and, as a consequence, in RNA-protein association and multimerization. We propose a model for the RNA-protein interaction, based on previous results and those presented in this study.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".