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BioMed Research International
Volume 2013 (2013), Article ID 704818, 9 pages
http://dx.doi.org/10.1155/2013/704818
Research Article

In Silico Expressed Sequence Tag Analysis in Identification of Probable Diabetic Genes as Virtual Therapeutic Targets

1Centre of Biotechnology, Siksha O Anusandhan University, Bhubaneswar, Odisha 751030, India
2Hi-Tech Research and Development Centre, Konark Institute of Science and Technology, Techno Park, Jatni, Bhubaneswar, Odisha 752050, India
3Department of Translational Research and Technology Development, Institute of Life Sciences, Nalco Square, Bhubaneswar, Odisha 751023, India

Received 25 September 2012; Revised 12 December 2012; Accepted 17 December 2012

Academic Editor: Ying Xu

Copyright © 2013 Pabitra Mohan Behera et al. 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.

Abstract

The expressed sequence tags (ESTs) are major entities for gene discovery, molecular transcripts, and single nucleotide polymorphism (SNPs) analysis as well as functional annotation of putative gene products. In our quest for identification of novel diabetic genes as virtual targets for type II diabetes, we searched various publicly available databases and found 7 reported genes. The in silico EST analysis of these reported genes produced 6 consensus contigs which illustrated some good matches to a number of chromosomes of the human genome. Again the conceptual translation of these contigs produced 3 protein sequences. The functional and structural annotations of these proteins revealed some important features which may lead to the discovery of novel therapeutic targets for the treatment of diabetes.