Evidence map›Paper›PMID 32388498›Full record

ArticleAging2020

Computational study of novel natural inhibitors targeting aminopeptidase N(CD13).

Junliang Ge, Zhongfeng Wang, Ye Cheng, Junan Ren, Bo Wu, Weihang Li, Xinhui Wang, Xing Su, Ziling Liu

Open access · greenAbstract read
In one paragraph

Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Junliang GeClinical College, Jilin University, Changchun, China.
Zhongfeng WangHepatopancreatobiliary Medicine Department, Jilin University First Hospital, Changchun, China.
Ye ChengDepartment of Neurosurgery, The Xuanwu Hospital Capital Medical University, Changchun, Beijing, China.
Junan RenDepartment of Orthopedics, The First Hospital of Jilin University, Changchun, China.
Bo WuClinical College, Jilin University, Changchun, China.
Weihang LiClinical College, Jilin University, Changchun, China.
Xinhui WangDepartment of Oncology, the First Hospital of Jilin University, Changchun, China.
Xing SuThe Laboratory of Cancer Precision Medicine, The First Hospital of Jilin University, Changchun, China.
Ziling LiuDepartment of Oncology, The First Hospital of Jilin University, Changchun, China.
First Hospital of Jilin University · CNJilin University · CNCapital Medical University · CNXijing Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition of aminopeptidase N(CD13) to contribute to medication design and development.

resultsTwo novel natural compounds, ZINC000000895551 and ZINC000014820583, from the ZINC15 database were found to have a higher binding affinity and more favorable interaction energy binding with CD13 with less rodent carcinogenicity, Ames mutagenicity, and non-inhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis suggested that the 2 complexes, ZINC000000895551-CD13 and ZINC000014820583-CD13, have favorable potential energy, and exist stably in the natural circumstances.

conclusionThis study discovered that ZINC000000895551 and ZINC000014820583 were ideal leading compounds to be inhibitions targeting to CD13. These compounds were selected as safe drug candidates as CD13 target medication design and improvement. MATERIALS AND

methodPotential inhibitors of CD13 were identified using a series of computer-aided structural and chemical virtual screening techniques. Structure-based virtual screening was carried out to calculate LibDock scores, followed by analyzing their absorption, distribution, metabolism, and excretion and toxicity predictions. Molecule docking was employed to reveal binding affinity between the selected compounds and CD13. Molecular dynamics simulation was applied to evaluate stability of the ligand-CD13 complex under natural environment.

Indexed as

Molecular Dynamics SimulationCD13 AntigensDatabases, FactualDrug Delivery SystemsDrug DiscoveryDrug Evaluation, PreclinicalHumansProtein BindingStructure-Activity RelationshipCD13 Antigensaminopeptidase N(CD13)bestatincancerdiscovery studio

Identifiers

PMID32388498
PMCPMC7244087
OpenAlexW3022830898

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.