An in silico approach in identification of drug targets in Leishmania: A subtractive genomic and metabolic simulation analysis. (April 2019)

• Record Type: Journal Article
• Authors: Meshram, Rohan J.; Goundge, Mayuri B.; Kolte, Baban S.; Gacche, Rajesh N.
• Is Part Of: Parasitology international. Volume 69(2019)
• Page Start: 59
• Page End: 70
• Publication Date: 2019-04
• Subjects: Leishmania -- Subtractive genomic -- Choke point analysis -- Metabolic simulations -- Drug targets -- Metabolic control analysis -- Druggability -- Threonine biosynthesis; Parasitology -- Periodicals; Parasites -- Periodicals; Parasitic Diseases -- Periodicals; Parasitology -- Periodicals; Parasitologie -- Périodiques; 571.99905
• DOI: 10.1016/j.parint.2018.11.006
• Languages: English
• ISSNs: 1383-5769

Abstract

Abstract: Leishmaniasis is one of the major health issue in developing countries. The current therapeutic regimen for this disease is less effective with lot of adverse effects thereby warranting an urgent need to develop not only new and selective drug candidates but also identification of effective drug targets. Here we present subtractive genomics procedure for identification of putative drug targets in Leishmania . Comprehensive druggability analysis has been carried out in the current work for identified metabolic pathways and drug targets. We also demonstrate effective metabolic simulation methodology to pinpoint putative drug targets in threonine biosynthesis pathway. Metabolic simulation data from the current study indicate that decreasing flux through homoserine kinase reaction can be considered as a good therapeutic opportunity. The data from current study is expected to show new avenue for designing experimental strategies in search of anti-leishmanial agents. Graphical abstract: Unlabelled Image Highlights: Subtractive genomic approach for drug target identification Durggability assessment of identified pathway Metabolic Simulation of identified pathway Effect of in silico inhibition of drug targets on metabolic pathway.