Arginase is an enzyme that catalyzes the formation of L-ornithine and urea from L-arginine. L-arginine is also a substrate for nitric oxide synthase (NOS), resulting in the formation of nitric oxide (NO) which is a key vasodilator. Not surprisingly, arginase inhibitors are being studied to treat various diseases, including hypertension, erectile dysfunction, atherosclerosis, wound healing and myocardial reperfusion injury. Recently, the use of virtual screening and docking to identify and characterize novel arginase inhibitors as potential therapeutics to treat leshmania infections has been reported in the literature. Hence, there is interest in the development of new and improved arginase inhibitors. Here, we describe the use of an iterative in silico and in vitro work-flow for identifying novel arginase inhibitors. The first in silico arm of the work-flow involves the use of library design, virtual screening, docking, and consensus scoring to identify predicted hit compounds. The in vitro arm involves rapid assaying of predicted hits in an optimized arginase assay. Confirmed hits are passed into the second in silico arm which involves ligand-based screening, docking, and consensus scoring. The crank is turned on the in silico – in vitro – in silico cycle until a promising candidate for hit-to-lead optimization has been identified. Preliminary results appear encouraging, providing hope that a novel arginase drug candidate will be identified and that our computational work-flow will prove useful on other targets.
Available at: http://works.bepress.com/benjamin_alper/13/