Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach
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 potent...
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Wiley
2014-01-01
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Series: | Journal of Diabetes Research |
Online Access: | http://dx.doi.org/10.1155/2014/763936 |
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author | Qiong Wang Zhigang Zhao Jing Shang Wei Xia |
author_facet | Qiong Wang Zhigang Zhao Jing Shang Wei Xia |
author_sort | Qiong Wang |
collection | DOAJ |
description | 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. |
format | Article |
id | doaj-art-d29d602436fb44d28cf779fb3173bf72 |
institution | Kabale University |
issn | 2314-6745 2314-6753 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Diabetes Research |
spelling | doaj-art-d29d602436fb44d28cf779fb3173bf722025-02-03T01:24:11ZengWileyJournal of Diabetes Research2314-67452314-67532014-01-01201410.1155/2014/763936763936Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics ApproachQiong Wang0Zhigang Zhao1Jing Shang2Wei Xia3Department of Endocrinology, Henan Provincial People’s Hospital, No. 7 Weiwu Road, Zhengzhou 450003, ChinaDepartment of Endocrinology, Henan Provincial People’s Hospital, No. 7 Weiwu Road, Zhengzhou 450003, ChinaDepartment of Endocrinology, Henan Provincial People’s Hospital, No. 7 Weiwu Road, Zhengzhou 450003, ChinaDepartment of Endocrinology, Henan Provincial People’s Hospital, No. 7 Weiwu Road, Zhengzhou 450003, ChinaWe 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.http://dx.doi.org/10.1155/2014/763936 |
spellingShingle | Qiong Wang Zhigang Zhao Jing Shang Wei Xia Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach Journal of Diabetes Research |
title | Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach |
title_full | Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach |
title_fullStr | Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach |
title_full_unstemmed | Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach |
title_short | Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach |
title_sort | targets and candidate agents for type 2 diabetes treatment with computational bioinformatics approach |
url | http://dx.doi.org/10.1155/2014/763936 |
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