Background: Mycobacterium tuberculosis (Mtb), the aetiological agent of tuberculosis, kills about 1.7 million people per year and is present in a latent form in about one-third of world's population. Glycosyltransferases and Glycosyl hydrolases catalyse the synthesis of important glycoconjugates, including glycolipids (PIM, LAM, and AG), glycoproteins, and polysaccharide offers the suitable drug targets. Drug repositioning provides immense opportunity and provides solutions for increasing time, cost and failure of novel drug discovery process. The pharmaceutical companies showed less interest in TB due to less profit in marketing and huge cost of developing a drug. Hence drug repositioning can be a alternative way to fight against TB. Here we have used computational functional genomics method to predict the novel carbohydrate active enzymes from Mtb genome, followed by drug repositioning of the selected genes based on their involvement in TB latency. Methods: The functional re-annotation of glycogenome of M.tuberculosis H37Rv on computational functional genomics, fold recognition methods was performed. 14 glycome related genes reported as top 500 ranked genes in latency by TargetDB (Dac B1, PurF, Rv0486, Rv0648, Rv1082, Rv1090, Rv1170, Rv1987, Rv2006, Rv2188c, Rv2402, Rv3487c, Rv1922, and Rv2619c) were selected. The structure of the proteins was modelled using Modeler 9v9. The network of TB co-infection with other diseases based on the epidemiological literature available between year 1966-2012 was created using Cytoscape and drugs used for those indications were used for docking analysis. Results: The functional re-annotation of glycogenome of M.tuberculosis H37Rv revealed ∼260 new glycome related genes including several GTs, GH, and secreted glycoproteins important for cell wall biosynthesis, virulence and other cellular metabolism. The epidemiological data suggested co-existence and reactivation of latent tuberculosis during chronic disorders and immunocompromised individuals with opportunistic infections. The anti-diabetic drugs, nucleotide analogs used for cancer treatment, HIV, protozoan disease showed novel interaction with the TB drug targets. Conclusion: The chance of Disease-Target-Drug interaction during this co-infection was more and exemplifies the survival strategy of tuberculosis infection. This knowledge driven drug repositioning strategy following understanding of interacting diseases can be effectively applied for the treatment for tuberculosis.