Journal of Bioinformatics and Sequence Analysis
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Article Number - FECF9C959898


Vol.8(1), pp. 1-11 , July 2016
DOI: 10.5897/JBSA2015.0101
ISSN: 2141-2464



Full Length Research Paper

In silico characterization of beta-galactosidase using computational tools



Gangadhar. C. Gouripur
  • Gangadhar. C. Gouripur
  • Department of Studies and Research in Biotechnology and Microbiology, Karnatak University, Dharwad - 580 003, India.
  • Google Scholar
Rohit. B. Kaliwal
  • Rohit. B. Kaliwal
  • Department of MCA, Vishwsvaraya Technological University, P.G Centre Regional Office, Gulbarga- 585106, India.
  • Google Scholar
Basappa. B. Kaliwal
  • Basappa. B. Kaliwal
  • Department of Studies in Biotechnology and Microbiology, Karnatak University, Dharwad, Karnataka, India.
  • Google Scholar







 Received: 21 February 2015  Accepted: 25 August 2015  Published: 31 July 2016

Copyright © 2016 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0


β-galactosidase (EC.3.2.1.23) is an important enzyme, mainly used in the preparation of lactose hydrolyzed milk suitable for people with lactose intolerance. It is essential to understand the structural and functional aspects of various β-galactosidase produced from different sources. The present work deals with the use of bioinformatics to describe the physiochemical, functional and structural properties of β-galactosidase enzymes on Bacillus sp. selected from the gene bank of NCBI. The grand average hydropathy (GRAVY) and low range of AFY63015.1 value indicates the possibility of better interaction with water and instability index were computed to characterise YP_004205251.1, ZP_10511829.1, BAL72724.1, AFY63015.1, NP_242888.1 stating that they are stable and disulfide bridges, CYS_REC recognizes the presence of 38 cysteine residues in β-galactosidase sequences and predicted most probable SS bond patterns of pairs in YP_004981461 and 1AFY63015.1. The self- optimized prediction method (SOPM) was used to predict the secondary structure. The SOPM results indicated the presence of alpha helix is more dominated in sequences AFY63015.1 and YP_004981461.1. Overall this represents in silico analysis of sequence, structural and functional information of β-galactosidase of Bacillus species.
 
Key words: Bacillus sp., β-galactosidase, in silico analysis, physico-chemical characterization, proteomics tools.

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APA Gouripur, G. C., Kaliwal, R. B., & Kaliwal, B. B. (2016). In silico characterization of beta-galactosidase using computational tools. Journal of Bioinformatics and Sequence Analysis, 8(1), 1-11.
Chicago Gangadhar. C. Gouripur, Rohit. B. Kaliwal and Basappa. B. Kaliwal,. "In silico characterization of beta-galactosidase using computational tools." Journal of Bioinformatics and Sequence Analysis 8, no. 1 (2016): 1-11.
MLA Gangadhar. C. Gouripur, et al. "In silico characterization of beta-galactosidase using computational tools." Journal of Bioinformatics and Sequence Analysis 8.1 (2016): 1-11.
   
DOI 10.5897/JBSA2015.0101
URL http://academicjournals.org/journal/JBSA/article-abstract/FECF9C959898

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