Docking-based virtual screening of known drugs against murE of Mycobacterium tuberculosis towards repurposing for TB.

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

BARLERIA MONTANA WIGHT AND NEES–A PROMISING NATURAL ANTI-INFLAMMATORY AGENT AGAINST FORMALIN INDUCED INFLAMMATION

Objective: To evaluate the anti-inflammatory activity of the ethanolic leaf extract of Barleria montana (B. montana) against formalin induced inflammation.Methods: Male albino wistar rats were pretreated with oral doses of 100 mg, 200 mg and 300 mg of the extract for 30 days and the animals received a single dose of sub plantar injection of formalin (0.1 ml/kg body weight (bw.)) Indomethacin (25 mg/kg bw.) was used as the standard drug. The effect of the extract on paw thickness, biochemical and hematological parameters was investigated along with histopathological studies.Results: The results revealed that the extract exhibited an effective dose dependent activity against formalin induced inflammation with a maximum activity at a dosage of 300 mg/kg bw. which was comparable with the standard drug.Conclusion: The results signify promising activity of ethanolic leaf extract of B. montana against formalin induced inflammation in albino rats. The extract was also found to exhibit appreciable antioxidant activity.Â

Azlocillin can be the potential drug candidate against drug-tolerant Borrelia burgdorferi sensu stricto JLB31.

Lyme disease is one of most common vector-borne diseases, reporting more than 300,000 cases annually in the United States. Treating Lyme disease during its initial stages with traditional tetracycline antibiotics is effective. However, 10-20% of patients treated with antibiotic therapy still shows prolonged symptoms of fatigue, musculoskeletal pain, and perceived cognitive impairment. When these symptoms persists for more than 6 months to years after completing conventional antibiotics treatment are called post-treatment Lyme disease syndrome (PTLDS). Though the exact reason for the prolongation of post treatment symptoms are not known, the growing evidence from recent studies suggests it might be due to the existence of drug-tolerant persisters. In order to identify effective drug molecules that kill drug-tolerant borrelia we have tested two antibiotics, azlocillin and cefotaxime that were identified by us earlier. The in vitro efficacy studies of azlocillin and cefotaxime on drug-tolerant persisters were done by semisolid plating method. The results obtained were compared with one of the currently prescribed antibiotic doxycycline. We found that azlocillin completely kills late log phase and 7-10 days old stationary phase B. burgdorferi. Our results also demonstrate that azlocillin and cefotaxime can effectively kill in vitro doxycycline-tolerant B. burgdorferi. Moreover, the combination drug treatment of azlocillin and cefotaxime effectively killed doxycycline-tolerant B. burgdorferi. Furthermore, when tested in vivo, azlocillin has shown good efficacy against B. burgdorferi in mice model. These seminal findings strongly suggests that azlocillin can be effective in treating B. burgdorferi sensu stricto JLB31 infection and furthermore in depth research is necessary to evaluate its potential use for Lyme disease therapy

DDTRP: Database of Drug Targets for Resistant Pathogens

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

DrugMechDB: A Curated Database of Drug Mechanisms

Abstract Computational drug repositioning methods have emerged as an attractive and effective solution to find new candidates for existing therapies, reducing the time and cost of drug development. Repositioning methods based on biomedical knowledge graphs typically offer useful supporting biological evidence. This evidence is based on reasoning chains or subgraphs that connect a drug to a disease prediction. However, there are no databases of drug mechanisms that can be used to train and evaluate such methods. Here, we introduce the Drug Mechanism Database (DrugMechDB), a manually curated database that describes drug mechanisms as paths through a knowledge graph. DrugMechDB integrates a diverse range of authoritative free-text resources to describe 4,583 drug indications with 32,249 relationships, representing 14 major biological scales. DrugMechDB can be employed as a benchmark dataset for assessing computational drug repositioning models or as a valuable resource for training such models