Evidence map›Paper›PMID 28689146›Full record

ReviewCurrent opinion in chemical biology2017

Chemical modulators for epigenome reader domains as emerging epigenetic therapies for cancer and inflammation.

Nilesh Zaware, Ming-Ming Zhou

Open access · greenAbstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

29 citing papers in PubMed, 50 citations in OpenAlex.

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  15. AnArtificial intelligence in the life sciences · 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

2 authors at 1 institution in 1 country.

Nilesh ZawareDepartment of Pharmacological Sciences, Icahn School of Medicine at Mt. Sinai, 1425 Madison Avenue, New York, NY 10029, United States.
Ming-Ming ZhouDepartment of Pharmacological Sciences, Icahn School of Medicine at Mt. Sinai, 1425 Madison Avenue, New York, NY 10029, United States. Electronic address: Ming-Ming.Zhou@mssm.edu.
Icahn School of Medicine at Mount Sinai · US

Funding

STRUCTURE OF PROTEIN MODULES IN CHROMATIN REMODELINGR01CA087658 · NCI · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI ZHOU, MING-MING · 2000 to 2016
$4.8M
Mechanism of BET Proteins in Th17 Cell DifferentiationR01AI124465 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ZHOU, MING-MING · 2016 to 2020
$2.9M
New Epigenetic Gene Silencing TechnologyR01GM119189 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI WALSH, MARTIN JOHN, ZHOU, MING-MING · 2016 to 2019
$1.8M
NCI NIH HHS R01 CA087658NIAID NIH HHS R01 AI124465NIGMS NIH HHS R01 GM119189
6 · The paper itself

Abstract

Site-specific lysine acetylation and methylation on histones are critical post-translational modifications (PTMs) that govern ordered gene transcription in chromatin. Mis-regulation of these histone PTM-mediated processes has been shown to be associated with human diseases. Since the 2010 landmark reports of small molecules (+)-JQ1 and I-BET762 that target the acetyl-lysine 'reader' Bromodomain and Extra Terminal domain (BET) proteins, there have been relentless efforts to develop epigenetic therapy with small molecules to modulate molecular interactions of epigenome reader domain proteins with PTMs. In addition to BET, the other emerging targets include non-BET acetyl-lysine and methyl-lysine reader domains. This review covers the key chemical modulators of the aforementioned epigenome reader proteins.

Indexed as

GenomicsEpigenesis, GeneticHumansInflammationLysineNeoplasmsLysine

Identifiers

PMID28689146
PMCPMC5581715
OpenAlexW2725543140

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.