Evidence map›Paper›PMID 32405248›Full record

ArticleDrug discovery today2020

SCHOOL of nature: ligand-independent immunomodulatory peptides.

Alexander B Sigalov

Abstract read
In one paragraph

Article in Drug discovery today, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. TREM-1 Modulation Strategies for Sepsis.Frontiers in immunology · 2022
    Review
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

1 author.

Alexander B SigalovSignaBlok, Inc., Shrewsbury, MA, USA. Electronic address: sigalov@signablok.com.

Funding

First-in-class TREM-1 inhibitors in combination therapy for pancreatic cancerR44CA217400 · NCI · SIGNABLOK, INC. · PI SIGALOV, ALEXANDER B · 2019 to 2020
$2.0M
First-in-class TREM-1 inhibitors in combination therapy for pancreatic cancerR43CA217400 · NCI · SIGNABLOK, INC. · PI SIGALOV, ALEXANDER B · 2017 to 2019
$227k
Development of first-in-class TREM-1 inhibitors for neovascular retinal diseasesR43EY028779 · NEI · SIGNABLOK, INC. · PI SIGALOV, ALEXANDER B · 2018 to 2018
$226k
Novel TREM-1 targeting therapies for sepsisR43GM128369 · NIGMS · SIGNABLOK, INC. · PI SIGALOV, ALEXANDER B · 2018 to 2018
$225k
NCI NIH HHS R43 CA217400NCI NIH HHS R44 CA217400NEI NIH HHS R43 EY028779NIGMS NIH HHS R43 GM128369
6 · The paper itself

Abstract

Groundbreaking studies in protein biophysics have identified the mechanisms of transmembrane signaling at the level of druggable protein-protein interactions (PPIs). This resulted in the development of the signaling chain homooligomerization (SCHOOL) strategy to modulate cell responses using receptor-specific peptides. Inspired by nature, these short peptides use ligand-independent mechanisms of receptor inhibition and demonstrate potent efficacy in vitro and in vivo. The SCHOOL strategy is especially important when receptor ligands are unknown. An example is the triggering receptor expressed on myeloid cells-1 (TREM-1) receptor, an emerging therapeutic target involved in the pathogenesis of most inflammatory diseases. Here, I discuss advances in the field with a focus on TREM-1 inhibitory SCHOOL peptides that offer new hope for a 'magic bullet' cure for cancer, arthritis, sepsis, retinopathy, and other medical challenges.

Indexed as

AnimalsArthritisHumansImmunologic FactorsLigandsNeoplasmsPeptidesRetinal DiseasesSepsisTriggering Receptor Expressed on Myeloid Cells-1Immunologic FactorsLigandsPeptidesTriggering Receptor Expressed on Myeloid Cells-1

Identifiers

PMID32405248
PMCPMC7217646

What OpenQuestion holds

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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.