Evidence map›Paper›PMID 36387821›Full record

ArticleWorld journal of clinical cases2022

Screening of traditional Chinese medicine monomers as ribonucleotide reductase M2 inhibitors for tumor treatment.

Ya-Ya Qin, Song Feng, Xiao-Dong Zhang, Bin Peng

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 60% 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

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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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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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

4 authors at 1 institution in 1 country.

Ya-Ya QinDepartment of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China.
Song FengSchool of Basic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan Province, China.
Xiao-Dong ZhangDepartment of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China.
Bin PengSchool of Basic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan Province, China. binpeng01@sina.com.
North Sichuan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRibonucleotide reductase (RR) is a key enzyme in tumor proliferation, especially its subunit-RRM2. Although there are multiple therapeutics for tumors, they all have certain limitations. Given their advantages, traditional Chinese medicine (TCM) monomers have become an important source of anti-tumor drugs. Therefore, screening and analysis of TCM monomers with RRM2 inhibition can provide a reference for further anti-tumor drug development.

aimTo screen and analyze potential anti-tumor TCM monomers with a good binding capacity to RRM2.

methodsThe Gene Expression Profiling Interactive Analysis database was used to analyze the level of RRM2 gene expression in normal and tumor tissues as well as RRM2's effect on the overall survival rate of tumor patients. TCM monomers that potentially act on RRM2 were screened

resultsThe expression of RRM2 mRNA in multiple tumor tissues was significantly higher than that in normal tissues, and it was negatively correlated with the overall survival rate of patients with the majority of tumor types. Through literature mining, we discovered that berberine, ursolic acid, gambogic acid, cinobufagin, quercetin, daphnetin, and osalmide have inhibitory effects on RRM2. The results of molecular docking identified that the above TCM monomers have a strong binding capacity with RRM2 protein, which mainly interacted through hydrogen bonds and hydrophobic force. The main binding sites were Arg330, Tyr323, Ser263, and Met350.

conclusionRRM2 is an important tumor therapeutic target. The TCM monomers screened have a good binding capacity with the RRM2 protein.

Indexed as

Literature miningMolecular dockingMonomerRibonucleotide reductase M2 inhibitorTraditional Chinese medicineTumor

Identifiers

PMID36387821
PMCPMC9649558
OpenAlexW4307560415

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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.