Title

Authors

Affiliation

¹Department of Bioinformatics, Karunya University, Coimbatore- 641114, India; ²Department of Biotechnology, Anna University of Technology, Coimbatore; ³CAS in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai.

Email

mohanasmail@gmail.com; *Corresponding author

Article Type

Hypothesis

Date

Received April 09, 2012; Accepted April 27, 2012; Published May 15, 2012

The emergence of HIV-TB co-infection and multi-drug resistant strains of Mycobacterium tuberculosis (Mtb) drive the need for new therapeutics against the infectious disease tuberculosis. Among the reported putative TB targets in the literature, the identification and characterization of the most probable therapeutic targets that influence the complex infectious disease, primarily through interactions with other influenced proteins, remains a statistical and computational challenge in proteomic epidemiology. Protein interaction network analysis provides an effective way to understand the relationships between protein products of genes by interconnecting networks of essential genes and its protein-protein interactions for 5 broad functional categories in Mtb. We also investigated the substructure of the protein interaction network and focused on highly connected nodes known as cliques by giving weight to the edges using data mining algorithms. Cliques containing Sulphate assimilation and Shikimate pathway enzymes appeared continuously inspite of increasing constraints applied by the K-Core algorithm during Network Decomposition. The potential target narrowed down through Systems approaches was Prephanate Dehydratase present in the Shikimate pathway which gives an insight to develop novel potential inhibitors through Structure Based Drug Design with natural compounds.

Keywords

Protein interaction network, Mycobacterium tuberculosis, Shikimate pathway, Systems approach.

Citation

Raman et al. Bioinformation 8(9): 403-406 (2012)
 

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.