Evidence map›Paper›PMID 38866895›Full record

ArticleScientific reports2024

Prediction of the binding mechanism of a selective DNA methyltransferase 3A inhibitor by molecular simulation.

Genki Kudo, Takumi Hirao, Ryuhei Harada, Takatsugu Hirokawa, Yasuteru Shigeta, Ryunosuke Yoshino

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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

6 authors.

Genki KudoPhysics Department, Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8571, Japan.
Takumi HiraoDoctoral Program in Medical Sciences, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Ibaraki, 305-8575, Japan.
Ryuhei HaradaCenter for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577, Japan.
Takatsugu HirokawaDivision of Biomedical Science, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan.
Yasuteru ShigetaPhysics Department, Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8571, Japan.
Ryunosuke YoshinoDivision of Biomedical Science, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. yoshino.r.aa@md.tsukuba.ac.jp.

Funding

Japan Agency for Medical Research and Development JP22ama121029j0002Japan Society for the Promotion of Science JP21K06094Japan Society for the Promotion of Science JP23K16987Ministry of Education, Culture, Sports, Science and Technology JPMXP1020230120
6 · The paper itself

Abstract

DNA methylation is an epigenetic mechanism that introduces a methyl group at the C5 position of cytosine. This reaction is catalyzed by DNA methyltransferases (DNMTs) and is essential for the regulation of gene transcription. The DNMT1 and DNMT3A or -3B family proteins are known targets for the inhibition of DNA hypermethylation in cancer cells. A selective non-nucleoside DNMT3A inhibitor was developed that mimics S-adenosyl-l-methionine and deoxycytidine; however, the mechanism of selectivity is unclear because the inhibitor-protein complex structure determination is absent. Therefore, we performed docking and molecular dynamics simulations to predict the structure of the complex formed by the association between DNMT3A and the selective inhibitor. Our simulations, binding free energy decomposition analysis, structural isoform comparison, and residue scanning showed that Arg688 of DNMT3A is involved in the interaction with this inhibitor, as evidenced by its significant contribution to the binding free energy. The presence of Asn1192 at the corresponding residues in DNMT1 results in a loss of affinity for the inhibitor, suggesting that the interactions mediated by Arg688 in DNMT3A are essential for selectivity. Our findings can be applied in the design of DNMT-selective inhibitors and methylation-specific drug optimization procedures.

Indexed as

DNA (Cytosine-5-)-MethyltransferasesDNA Methyltransferase 3AEnzyme InhibitorsMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingBinding SitesDNA (Cytosine-5-)-Methyltransferase 1DNA MethylationHumansDNA (Cytosine-5-)-Methyltransferase 1DNA (Cytosine-5-)-MethyltransferasesDNA Methyltransferase 3ADNMT1 protein, humanDNMT3A protein, humanEnzyme InhibitorsDNA methyltransferaseDNMT3AMolecular dynamics simulationProtein inhibitorSelective inhibitor

Identifiers

PMID38866895
PMCPMC11169543

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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.