Evidence map›Paper›PMID 26716901›Full record

ArticleOncotarget2016

The drug target genes show higher evolutionary conservation than non-target genes.

Wenhua Lv, Yongdeng Xu, Yiying Guo, Ziqi Yu, Guanglong Feng, Panpan Liu, Meiwei Luan, Hongjie Zhu, Guiyou Liu, Mingming Zhang and 6 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  8. Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes.Proceedings of the National Academy of Sciences of the United States of America · 2018
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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

16 authors.

Wenhua LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yongdeng XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yiying GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ziqi YuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Guanglong FengDepartment of Radiology, Second Affiliated Hospital, Harbin Medical University, Harbin, China.
Panpan LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Meiwei LuanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hongjie ZhuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Guiyou LiuGenome Analysis Laboratory, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
Mingming ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hongchao LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Lian DuanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Zhenwei ShangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jin LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yongshuai JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ruijie ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although evidence indicates that drug target genes share some common evolutionary features, there have been few studies analyzing evolutionary features of drug targets from an overall level. Therefore, we conducted an analysis which aimed to investigate the evolutionary characteristics of drug target genes. We compared the evolutionary conservation between human drug target genes and non-target genes by combining both the evolutionary features and network topological properties in human protein-protein interaction network. The evolution rate, conservation score and the percentage of orthologous genes of 21 species were included in our study. Meanwhile, four topological features including the average shortest path length, betweenness centrality, clustering coefficient and degree were considered for comparison analysis. Then we got four results as following: compared with non-drug target genes, 1) drug target genes had lower evolutionary rates; 2) drug target genes had higher conservation scores; 3) drug target genes had higher percentages of orthologous genes and 4) drug target genes had a tighter network structure including higher degrees, betweenness centrality, clustering coefficients and lower average shortest path lengths. These results demonstrate that drug target genes are more evolutionarily conserved than non-drug target genes. We hope that our study will provide valuable information for other researchers who are interested in evolutionary conservation of drug targets.

Indexed as

Databases, FactualEvolution, MolecularGene OntologyModels, BiologicalConserved SequenceGenesGenome, HumanHumansLinkage DisequilibriumPharmaceutical PreparationsProtein Interaction MapsPharmaceutical Preparationsdrug targetevolutionary conservationtopological properties

Identifiers

PMID26716901
PMCPMC4826257

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Registered trials

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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.