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. 2011:2011:801478.
doi: 10.1155/2011/801478. Epub 2011 Nov 29.

Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification

Gaston K Mazandu  1 , Nicola J Mulder
Affiliations

Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification

Gaston K Mazandu et al. Adv Bioinformatics. 2011.

Abstract

Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying potential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets, functional interaction networks between proteins are used to identify proteins essential to the survival, growth, and virulence of these microbial pathogens. Here we have integrated functional genomics data to generate functional interaction networks between Mycobacterium tuberculosis proteins and carried out computational analyses to dissect the functional interaction network produced for identifying drug targets using network topological properties. This study has provided the opportunity to expand the range of potential drug targets and to move towards optimal target-based strategies.

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Figures

Figure 1
Figure 1
Data integration scheme.
Figure 2
Figure 2
Distribution of shortest path lengths between reachable pair-wise protein functional interactions.
Figure 3
Figure 3
Connectivity distribution of detected k functional links per protein, plotted as a function of frequency 𝒫(k).
Figure 4
Figure 4
Assessing network vulnerability under random and targeted attacks.
Figure 5
Figure 5
Analyzing the variations in the betweenness metric in terms of protein category.
Figure 6
Figure 6
Assessing the variations in closeness and confidence centrality measures in terms of protein category.
Figure 7
Figure 7
Distribution of candidate drug targets per functional class.
Figure 8
Figure 8
An illustration of a structural hub protein. Nodes are coloured by functional class: virulence (light-green), PE/PPE (yellow), cell wall and cell processes (green), lipid metabolism (light-blue), intermediary metabolism and respiration (grey), and unknown (white).
See this image and copyright information in PMC

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