Inhibition of the Nef regulatory protein of HIV-1 by a single-domain antibody
Bibliographic record
Abstract
The Nef protein of HIV-1 is important for AIDS pathogenesis, but it is not targeted by current antiviral strategies. Here, we describe a single-domain antibody (sdAb) that binds to HIV-1 Nef with a high affinity (K(d) = 2 × 10(-9)M) and inhibited critical biologic activities of Nef both in vitro and in vivo. First, it interfered with the CD4 down-regulation activity of a broad panel of nef alleles through inhibition of the Nef effects on CD4 internalization from the cell surface. Second, it was able to interfere with the association of Nef with the cellular p21-activated kinase 2 as well as with the resulting inhibitory effect of Nef on actin remodeling. Third, it counteracted the Nef-dependent enhancement of virion infectivity and inhibited the positive effect of Nef on virus replication in peripheral blood mononuclear cells. Fourth, anti-Nef sdAb rescued Nef-mediated thymic CD4(+) T-cell maturation defects and peripheral CD4(+) T-cell activation in the CD4C/HIV-1(Nef) transgenic mouse model. Because all these Nef functions have been implicated in Nef effects on pathogenesis, this anti-Nef sdAb may represent an efficient tool to elucidate the molecular functions of Nef in the virus life cycle and could now help to develop new strategies for the control of AIDS.
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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 | 0.001 |
| 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".