Cargando…
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...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221868/ https://www.ncbi.nlm.nih.gov/pubmed/25401107 http://dx.doi.org/10.1155/2014/763936 |
_version_ | 1782342940493873152 |
---|---|
author | Wang, Qiong Zhao, Zhigang Shang, Jing Xia, Wei |
author_facet | Wang, Qiong Zhao, Zhigang Shang, Jing Xia, Wei |
author_sort | Wang, Qiong |
collection | PubMed |
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 | Online Article Text |
id | pubmed-4221868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-42218682014-11-16 Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach Wang, Qiong Zhao, Zhigang Shang, Jing Xia, Wei J Diabetes Res Research Article 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. Hindawi Publishing Corporation 2014 2014-10-21 /pmc/articles/PMC4221868/ /pubmed/25401107 http://dx.doi.org/10.1155/2014/763936 Text en Copyright © 2014 Qiong Wang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Qiong Zhao, Zhigang Shang, Jing Xia, Wei Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach |
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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221868/ https://www.ncbi.nlm.nih.gov/pubmed/25401107 http://dx.doi.org/10.1155/2014/763936 |
work_keys_str_mv | AT wangqiong targetsandcandidateagentsfortype2diabetestreatmentwithcomputationalbioinformaticsapproach AT zhaozhigang targetsandcandidateagentsfortype2diabetestreatmentwithcomputationalbioinformaticsapproach AT shangjing targetsandcandidateagentsfortype2diabetestreatmentwithcomputationalbioinformaticsapproach AT xiawei targetsandcandidateagentsfortype2diabetestreatmentwithcomputationalbioinformaticsapproach |