Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach

Joint Authors

Wang, Qiong
Zhao, Zhigang
Shang, Jing
Xia, Wei

Source

Journal of Diabetes Research

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-10-21

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Diseases
Medicine

Abstract EN

We sought to explore the molecular mechanism of type 2 diabetes (T2D) and identify potential drug targets and candidate agents for T2D treatment.

The differentially expressed genes (DEGs) were assessed between human pancreatic islets with T2D and normal islets.

The dysfunctional pathways, the potential transcription factor, and microRNA targets were analyzed by bioinformatics methods.

Moreover, a group of bioactive small molecules were identified based on the connectivity map database.

The pathways of Eicosanoid Synthesis, TGF-beta signaling pathway, Prostaglandin Synthesis and Regulation, and Integrated Pancreatic Cancer Pathway were found to be significantly dysregulated in the progression of T2D.

The genes of ZADH2 (zinc binding alcohol dehydrogenase domain containing 2), BTBD3 (BTB (POZ) domain containing 3), Cul3-based ligases, LTBP1 (latent-transforming growth factor beta binding protein 1), PDGFRA (alpha-type platelet-derived growth factor receptor), and FST (follistatin) were determined to be significant nodes regulated by potential transcription factors and microRNAs.

Besides, two small molecules (sanguinarine and DL-thiorphan) were identified to be capable of reverse T2D.

In the present study, a systematic understanding for the mechanism underlying T2D development was provided with biological informatics methods.

The significant nodes and bioactive small molecules may be drug targets and candidate agents for T2D treatment.

American Psychological Association (APA)

Wang, Qiong& Zhao, Zhigang& Shang, Jing& Xia, Wei. 2014. Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach. Journal of Diabetes Research،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1040363

Modern Language Association (MLA)

Wang, Qiong…[et al.]. Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach. Journal of Diabetes Research No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1040363

American Medical Association (AMA)

Wang, Qiong& Zhao, Zhigang& Shang, Jing& Xia, Wei. Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach. Journal of Diabetes Research. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1040363

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1040363