Annual Research & Review in Biology

Fatty acid biosynthesis of Mycobacterium tuberculosis was analyzed using graph theory and minimum robust domination energy. The digraphs representing this Mycobacterial network provide crucial information regarding the connectivity of each protein or metabolite in a given pathway, providing an important tool into the significance of various components in the pathway, and this can be quantitatively analyzed. Using minimum robust domination energy of the network, the most influential set of proteins which when removed could cause a significant impact on the biosynthetic pathway, were identified. The metabolic network was designed using the KEGG LIGAND database and subjected to graph theory analysis. In the present study minimum robust domination energy of the network was analysed. The minimum robust domination energy of a protein network was used to determine the influence of the said protein on other components in the network. Set of most influential vertices in the network has less robust energy than minimum robust domination energy of the network. Therefore, the most strategic vertices will be the vertices of the influential set which when eliminated will cause maximum disruptions to the metabolic network of this deadly pathogen. This will require lesser energy than the targeted vertices (proteins) of the minimal dominating set.