Evidence map›Paper›PMID 32525297›Full record

ArticleACS combinatorial science2020

Optimization of High-Throughput Methyltransferase Assays for the Discovery of Small Molecule Inhibitors.

Guangping Dong, Adam Yasgar, Darrell L Peterson, Alexey Zakharov, Daniel Talley, Ken Chih-Chien Cheng, Ajit Jadhav, Anton Simeonov, Rong Huang

Open access · greenAbstract read
In one paragraph

Article in ACS combinatorial science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

  1. ACS medicinal chemistry letters · 2026
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  2. Inhibition ofACS omega · 2025
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  3. Review
  4. Inhibition ofbioRxiv : the preprint server for biology · 2025
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  8. Article
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  11. Article
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  13. Article
  14. Mechanisms and inhibitors of nicotinamideRSC medicinal chemistry · 2021
    Review
  15. Article
  16. Development of A Continuous Fluorescence-Based Assay forInternational journal of molecular sciences · 2021
    Article
  17. Article
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

9 authors at 2 institutions in 1 country.

Guangping DongDepartment of Medicinal Chemistry and Molecular Pharmacology, Center for Cancer Research, Institute for Drug Discovery, Purdue University, West Lafayette, Indiana 47907, United States.
Adam YasgarNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20892, United States.ORCID 0000-0001-7350-1402
Darrell L PetersonDepartment of Biochemistry, Institute for Structural Biology, Drug Discovery and Development, Virginia Commonwealth University, Richmond, Virginia 23219, United States.
Alexey ZakharovNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20892, United States.ORCID 0000-0003-2466-1711
Daniel TalleyNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20892, United States.
Ken Chih-Chien ChengNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20892, United States.
Ajit JadhavNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20892, United States.
Anton SimeonovNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland 20892, United States.
Rong HuangDepartment of Medicinal Chemistry and Molecular Pharmacology, Center for Cancer Research, Institute for Drug Discovery, Purdue University, West Lafayette, Indiana 47907, United States.ORCID 0000-0002-1477-3165
National Institutes of Health · USVirginia Commonwealth University · US

Funding

Transgenic Mouse Core Facility Shared Resource (TMCF-SR)P30CA023168 · NCI · PURDUE UNIVERSITY WEST LAFAYETTE · PI Andrea L Kasinski · 1985 to 2026
$43.4M
Discovery of small molecule inhibitors for protein N-terminal methyltransferaseU01CA214649 · NCI · PURDUE UNIVERSITY · PI HUANG, RONG · 2017 to 2019
$1.1M
NCI NIH HHS P30 CA023168NCI NIH HHS U01 CA214649
6 · The paper itself

Abstract

Methyltransferases (MTases) play diverse roles in cellular processes. Aberrant methylation levels have been implicated in many diseases, indicating the need for the identification and development of small molecule inhibitors for each MTase. Specific inhibitors can serve as probes to investigate the function and validate therapeutic potential for the respective MTase. High-throughput screening (HTS) is a powerful method to identify initial hits for further optimization. Here, we report the development of a fluorescence-based MTase assay and compare this format with the recently developed MTase-Glo luminescence assay for application in HTS. Using protein N-terminal methyltransferase 1 (NTMT1) as a model system, we miniaturized to 1536-well quantitative HTS format. Through a pilot screen of 1428 pharmacologically active compounds and subsequent validation, we discovered that MTase-Glo produced lower false positive rates than the fluorescence-based MTase assay. Nevertheless, both assays displayed robust performance along with low reagent requirements and can potentially be employed as general HTS formats for the discovery of inhibitors for any MTase.

Indexed as

Drug DiscoveryHigh-Throughput Screening AssaysEnzyme InhibitorsHumansMethyltransferasesMolecular StructureSmall Molecule LibrariesEnzyme InhibitorsMethyltransferasesNTMT1 protein, humanSmall Molecule Librariesassay miniaturizationhigh-throughput screeningmethyltransferase inhibitorsprotein N-terminal methyltransferase 1SAHH-coupled fluorescence assay

Identifiers

PMID32525297
PMCPMC7429283
OpenAlexW3033418505

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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.