Evidence map›Paper›PMID 24832514›Full record

ArticleBiology2012

Strategies to Block HIV Transcription: Focus on Small Molecule Tat Inhibitors.

Guillaume Mousseau, Susana Valente

Open access · goldAbstract read
In one paragraph

Article in Biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
0.8field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 38 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Guillaume MousseauDepartment of Infectious Diseases, The Scripps Research Institute, Scripps Florida, 130 Scripps Way, Jupiter, FL 33458, USA. mousseau@scripps.edu.
Susana ValenteDepartment of Infectious Diseases, The Scripps Research Institute, Scripps Florida, 130 Scripps Way, Jupiter, FL 33458, USA. svalente@scripps.edu.
Scripps Research Institute · US

Funding

Mode of action of a new Tat HIV-1 inhibitorR01AI097012 · NIAID · UNIVERSITY OF FLORIDA · PI VALENTE, SUSANA T · 2012 to 2022
$7.5M
NIAID NIH HHS R01 AI097012
6 · The paper itself

Abstract

After entry into the target cell, the human immunodeficiency virus type I (HIV) integrates into the host genome and becomes a proviral eukaryotic transcriptional unit. Transcriptional regulation of provirus gene expression is critical for HIV replication. Basal transcription from the integrated HIV promoter is very low in the absence of the HIV transactivator of transcription (Tat) protein and is solely dependent on cellular transcription factors. The 5' terminal region (+1 to +59) of all HIV mRNAs forms an identical stem-bulge-loop structure called the Transactivation Responsive (TAR) element. Once Tat is made, it binds to TAR and drastically activates transcription from the HIV LTR promoter. Mutations in either the Tat protein or TAR sequence usually affect HIV replication, indicating a strong requirement for their conservation. The necessity of the Tat-mediated transactivation cascade for robust HIV replication renders Tat one of the most desirable targets for transcriptional therapy against HIV replication. Screening based on inhibition of the Tat-TAR interaction has identified a number of potential compounds, but none of them are currently used as therapeutics, partly because these agents are not easily delivered for an efficient therapy, emphasizing the need for small molecule compounds. Here we will give an overview of the different strategies used to inhibit HIV transcription and review the current repertoire of small molecular weight compounds that target HIV transcription.

Identifiers

PMID24832514
PMCPMC4009808
OpenAlexW1997801681

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.