ABSTRACT
New drugs are urgently needed to cure tuberculosis (TB) in a short period of time without causing any adverse effects since currently used drugs for the treatment of multi drug-resistant TB cause several adverse effects with poor success rate. Therefore, we aimed to prioritize known drugs towards repurposing for TB by employing bioinformatics approach in the present study. A total of 1554 FDA approved drugs were obtained from DrugBank. Serine/threonine-protein kinase, pknB (Rv0014c) of Mycobacterium tuberculosis (Mtb) was selected as the drug target since it involves in several vital functions of the Mtb. All of the 1554 drugs were subjected to molecular docking with pknB. Glide and AutoDock Vina were employed using rigid docking followed by induced fit docking protocol for prioritization of drugs. Out of 14 drugs prioritized, six are suggested as high-confident drugs towards repurposing for TB as they were consistently found within top 10 ranks of both methods, and strongly binding in the active site of the pknB. We also found atorvastatin as one of the high-confident drugs, which has already been demonstrated to be active against Mtb under in vitro conditions by other researchers. Therefore, we propose that the prioritized six high-confident drugs as potential candidates for repurposing for TB and suggest for further experimental studies. We also suggest that the bioinformatics procedure we have employed in this study could be effectively applied for prioritization of drugs for other diseases.
Subject(s)
Computational Biology/methods , Drug Repositioning , Tuberculosis/drug therapy , Atorvastatin/pharmacology , Drug Approval , Humans , Models, Molecular , Molecular Docking Simulation , Mycobacterium tuberculosis/drug effects , Protein Conformation , Protein Serine-Threonine Kinases/metabolism , United States , United States Food and Drug AdministrationABSTRACT
Repurposing has gained momentum globally and become an alternative avenue for drug discovery because of its better success rate, and reduced cost, time and issues related to safety than the conventional drug discovery process. Several drugs have already been successfully repurposed for other clinical conditions including drug resistant tuberculosis (DR-TB). Though TB can be cured completely with the use of currently available anti-tubercular drugs, emergence of drug resistant strains of Mycobacterium tuberculosis and the huge death toll globally, together necessitate urgently newer and effective drugs for TB. Therefore, we performed virtual screening of 1554 FDA approved drugs against murE, which is essential for peptidoglycan biosynthesis of M. tuberculosis. We used Glide and AutoDock Vina for virtual screening and applied rigid docking algorithm followed by induced fit docking algorithm in order to enhance the quality of the docking prediction and to prioritize drugs for repurposing. We found 17 drugs binding strongly with murE and three of them, namely, lymecycline, acarbose and desmopressin were consistently present within top 10 ranks by both Glide and AutoDock Vina in the induced fit docking algorithm, which strongly indicates that these three drugs are potential candidates for further studies towards repurposing for TB.
ABSTRACT
Emergence of drug resistance is a major threat to public health. Many pathogens have developed resistance to most of the existing antibiotics, and multidrug-resistant and extensively drug resistant strains are extremely difficult to treat. This has resulted in an urgent need for novel drugs. We describe a database called 'Database of Drug Targets for Resistant Pathogens' (DDTRP). The database contains information on drugs with reported resistance, their respective targets, metabolic pathways involving these targets, and a list of potential alternate targets for seven pathogens. The database can be accessed freely at http://bmi.icmr.org.in/DDTRP.
