Three-dimensional models of Mycobacterium tuberculosis proteins Rv1555, Rv1554 and their docking analyses with sildenafil, tadalafil, vardenafil drugs, suggest interference with quinol binding likely to affect protein's function.

BACKGROUND: Earlier based on bioinformatics analyses, we had predicted the Mycobacterium tuberculosis (M.tb) proteins; Rv1555 and Rv1554, among the potential new tuberculosis drug targets. According to the 'TB-drugome' the Rv1555 protein is 'druggable' with sildenafil (Viagra), tadalafil (Cialis) and vardenafil (Levitra) drugs. In the present work, we intended to understand via computer modeling studies, how the above drugs are likely to inhibit the M.tb protein's function. RESULTS: The three-dimensional computer models for M.tb proteins; Rv1555 and Rv1554 constructed on the template of equivalent membrane anchor subunits of the homologous E.coli quinol fumarate reductase respiratory protein complex, followed by drug docking analyses, suggested that the binding of above drugs interferes with quinol binding sites. Also, we experimentally observed the in-vitro growth inhibition of E.coli bacteria containing the homologous M.tb protein sequences with sildenafil and tadalafil drugs. CONCLUSIONS: The predicted binding sites of the drugs is likely to affect the above M.tb proteins function as quinol binding is known to be essential for electron transfer function during anaerobic respiration in the homologous E.coli protein complex. Therefore, sildenafil and related drugs currently used in the treatment of male erectile dysfunction targeting the human phosphodiesterase 5 enzyme may be evaluated for their plausible role as repurposed drugs to treat human tuberculosis.

Comparative analyses of the proteins from Mycobacterium tuberculosis and human genomes: Identification of potential tuberculosis drug targets.

Tuberculosis, one of the major infectious diseases affecting human beings is caused by the bacillus Mycobacterium tuberculosis. Increased resistance to known drugs commonly used for the treatment of tuberculosis has created an urgent need to identify new targets for validation and to develop drugs. In this study, we have used various bioinformatics tools, to compare the protein sequences from twenty-three M. tuberculosis genome strains along with the known human protein sequences, in order to identify the 'conserved' M. tuberculosis proteins absent in human. Further, based on the analysis of protein interaction networks, we selected one-hundred and forty proteins that were predicted as potential M. tuberculosis drug targets and prioritized according to the ranking of 'clusters' of interacting proteins. Comparison of the predicted 140 TB targets with literature indicated that 46 of them were previously reported, thereby increasing the confidence in our predictions of the remaining 94 targets too. The analyses of the structures and functions corresponding to the predicted potential TB drug targets indicated a diverse range of proteins that included ten 'druggable' targets with some of the known drugs.