Evidence map›Paper›PMID 23503527›Full record

ReviewChemical Society reviews2013

Targeting Toll-like receptors with small molecule agents.

Xiaohui Wang, Christina Smith, Hang Yin

Abstract readReview
In one paragraph

Review in Chemical Society reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

46 citing papers in PubMed, 114 citations in OpenAlex.

  1. Bicuculline fromComputational and structural biotechnology journal · 2026
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  10. Serine-/Cysteine-Based spJournal of medicinal chemistry · 2023
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  16. Synthesis, structure-activity relationship studies and evaluation of a TLR 3/8/9 agonist and its analogues.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2021
    Article
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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

3 authors at 1 institution in 1 country.

Xiaohui WangDepartment of Chemistry and Biochemistry and the BioFrontiers Institute, 596 University of Colorado at Boulder, Boulder, CO 80309-0596, USA.
Christina Smith
Hang Yin
University of Colorado Boulder · US

Funding

Exogenous Chemical Probes of TLR-Mediated NeuroinflammationR01GM101279 · NIGMS · UNIVERSITY OF COLORADO · PI YIN, HANG HUBERT · 2013 to 2017
$1.4M
NIGMS NIH HHS GM101279NIGMS NIH HHS R01 GM101279
6 · The paper itself

Abstract

Toll-like receptors (TLRs) are type I transmembrane proteins that are key regulators of both innate and adaptive immune responses. To protect the host from viral and bacterial threats, TLRs trigger a pro-inflammatory immune response by detecting pathogen and danger associated molecular patterns. Considerable evidence has accumulated to show that the dysregulation of TLR signaling contributes to the development and progression of numerous diseases. Therefore, TLRs are emerging as important drug discovery targets. Currently, there is great interest in the development of TLR small molecule modulators for interrogating TLR signaling and treating diseases caused by TLR signaling malfunctions. In this tutorial review, we will outline methods for the discovery of TLR small molecule modulators and the up-to-date progress in this field. Small molecules targeting TLRs not only provide an opportunity to identify promising drug candidates, but also unveil knowledge regarding TLR signaling pathways.

Indexed as

Drug DesignHumansImmunity, InnateNitric OxideSignal TransductionToll-Like ReceptorsNitric OxideToll-Like Receptors

Identifiers

PMID23503527
PMCPMC3665707
OpenAlexW2075426423

What OpenQuestion holds

Textmetadata
LicenceTDM
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.