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Record W2048506561 · doi:10.1182/blood-2010-07-296749

Inhibition of the Nef regulatory protein of HIV-1 by a single-domain antibody

2011· article· en· W2048506561 on OpenAlexaff
Jérôme Bouchet, Stéphane Basmaciogullari, Pavel Chrobák, Bettina Stolp, Nathalie Bouchard, O. Fackler, Patrick Chames, Paul Jolicoeur, Serge Bénichou, Daniel Baty

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsSingle-domain antibodyInternalizationBiologyAntibodyIn vivoPathogenesisPeripheral blood mononuclear cellCell biologyIn vitroVirusVirologyViral replicationCellImmunologyGenetics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.220
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations70
Published2011
Admission routes1
Has abstractyes

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