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Title

BioDADPep: A Bioinformatics database for anti-diabetic peptides

Authors

Susanta Roy* & Robindra Teron

 

Affiliation

Department of Life Science and Bioinformatics, Assam University Diphu Campus, Diphu, Karbi Anglong 782 462, India

 

Email

Susanta Roy - Email: susantoroy@gmail.com

 

Article Type

Research Article

 

Date

Received October 19, 2019; Revised November 7, 2019; Accepted November 9, 2019; Published November 13, 2019

 

Abstract

The increasing number of cases for diabetes worldwide is a concern. Therefore, it is of interest to design therapeutic peptides to overcome side effects caused by the available drugs. It should be noted that data on several known anti-diabetic peptides is available in the literature in an organized manner. Hence, it is of interest to collect, glean and store such data in form of a searchable database supported by RDBMS. Data on anti-diabetic peptides and their related data are collected from the literature using manual search. Data on related peptides from other databases (THPdb, ADP3, LAMP, AHTPDB, AVPdb, BioPepDB, CancerPPD, CPPsite, DRAMP, SATPdb, CAMPR3 and MBPDB) are also included after adequate curation. Thus, we describe the development and utility of BioDADPep, a Bioinformatics database for antidiabetic peptides. The database has cross-reference for antidiabetic peptides. The database is enabled with a web-based GUI using a simple Google-like search function. Data presented in BioDADPep finds application in the design of an effective anti-diabetic peptide.

 

Keywords

Diabetes mellitus (DM), therapeutic protein targets, anti-diabetic peptides, text mining, peptide database, cross reactivity

 

Citation

Roy & Teron, Bioinformation 15(11): 780-783 (2019)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.