Evidence map›Paper›PMID 24645986›Full record

ArticleCell proliferation2014

Identification of novel kinase inhibitors by targeting a kinase-related apoptotic protein-protein interaction network in HeLa cells.

Z Shi, N An, B M Lu, N Zhou, S L Yang, B Zhang, C Y Li, Z J Wang, F Wang, C F Wu and 1 more

Abstract read
In one paragraph

Article in Cell proliferation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

6 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

11 authors at 2 institutions in 1 country.

Z ShiSchool of Life Sciences & Key Laboratory of Bio-resources, Ministry of Education, Sichuan University, Chengdu, 610064, China; School of Life Sciences, Guizhou Normal University, Guiyang, 550001, China.
N An
B M Lu
N Zhou
S L Yang
B Zhang
C Y Li
Z J Wang
F Wang
C F Wu
J K Bao
Sichuan University · CNGuizhou Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesProtein kinases orchestrate activation of signalling cascades in response to extra- and intracellular stimuli for regulation of cell proliferation. They are directly involved in a variety of diseases, particularly cancers. Systems biology approaches have become increasingly important in understanding regulatory frameworks in cancer, and thus may facilitate future anti-cancer discoveries. Moreover, it has been suggested and confirmed that high-throughput virtual screening provides a novel, effective way to reveal small molecule protein kinase inhibitors. Accordingly, we aimed to identify kinase targets and novel kinase inhibitors. MATERIALS AND

methodsA series of bioinformatics methods, such as network construction, molecular docking and microarray analyses were performed.

resultsIn this study, we computationally constructed the appropriate global human protein-protein interaction network with data from online databases, and then modified it into a kinase-related apoptotic protein-protein interaction network. Subsequently, we identified several kinases as potential drug targets according to their differential expression observed by microarray analyses. Then, we predicted relevant microRNAs, which could target the above-mentioned kinases. Ultimately, we virtually screened a number of small molecule natural products from Traditional Chinese Medicine (TCM)@Taiwan database and identified a number of compounds that are able to target polo-like kinase 1, cyclin-dependent kinase 1 and cyclin-dependent kinase 2 in HeLa cervical carcinoma cells.

conclusionsTaken together, all these findings might hopefully facilitate discovery of new kinase inhibitors that could be promising candidates for anti-cancer drug development.

Indexed as

Antineoplastic AgentsApoptosisCell Cycle ProteinsCell ProliferationCyclin-Dependent Kinase 2Databases, ProteinHeLa CellsHumansMicroRNAsMolecular Docking SimulationPolo-Like Kinase 1Protein Interaction MapsProtein Kinase InhibitorsProtein Serine-Threonine KinasesProtein Structure, TertiaryProto-Oncogene ProteinsAntineoplastic AgentsCDK2 protein, humanCell Cycle ProteinsCyclin-Dependent Kinase 2MicroRNAsPolo-Like Kinase 1Protein Kinase InhibitorsProtein Serine-Threonine KinasesProto-Oncogene Proteins

Identifiers

PMID24645986
PMCPMC6496802
OpenAlexW1979475524

What OpenQuestion holds

Textmetadata
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.