Journal of Computational Intelligence in Bioinformatics
  • Year: 2009
  • Volume: 2
  • Issue: 1and2

In Silico Analysis of Human Granulocyte Macrophage Colony Stimulating Factor (hGM-CSF) Gene to Increase the Stability of Gene Product – A Bioinformatics Approach

  • Author:
  • Balaji Somasundaram2, Bharath Ganesh Anantharaman2, Vishwanath Kumar Maharajapuram Ramachandran2, Swaminathan Detchanamurthy1,
  • Total Page Count: 13
  • Page Number: 47 to 59

1Department of Chemical and Process Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand-8140.

2Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, India-602105.

*Corresponding author Previous Affiliation: Bioprocess and Downstream Processing Laboratory, Department of Biotechnology, Sri Venkateswara College of Engineering, Sriperumbudur, Tamilnadu, India-602105.

Abstract

Granulocyte Macrophage Colony Stimulating Factor (GM-CSF) is one of the several naturally occurring glycoproteins that regulate leukocyte production, migration and function. It has been produced in different cell types and with different properties based on the production process. The objective of this work is to carry out the site-directed mutagenesis (in-silico analysis) in human Granulocyte Macrophage Colony Stimulating Factor in order to increase the stability and half-life of this protein without affecting its biological activity. Among the other GM-CSF's, Murine GM-CSF is the most stable form. Hence in this work, sequential analysis of the murine and human GM-CSF was performed in detail to understand the differences in the stability. It was found that the sialic acid content increased the half life of GM-CSF. Based on phylogenetic analysis and the information about the interaction of sialic acid, number of point mutations with Glutamic Acid (Glu), Asparagine (Asn), Arginine (Arg) were implemented at position 78 (Threonine-Thr) of hGM-CSF and studied the effect of these mutations using Bio-Informatics tools. Energy minimisation studies were carried out to identify the stability. These studies revealed the potential advantages of using Arg to increase the stability. Further, using Bio-Informatics tools such as PatchDock, Argus Lab and Hex the mutated GM-CSF was docked and analyzed for the bio-activity of hGM-CSF. The Arg mutation showed no change in the bioactivity. This Arg (−78) mutated GM-CSF can be confirmed for stability and biological activity using site- directed mutagenesis, in-vitro and in-vivo experiments.

Keywords

GM-CSF, in-silico, mutation, sialic acid, bioinformatics