Integrated Screening for Arginase Inhibitors

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

Computational Design of Novel Insulin Degrading Enzyme Inhibitors

Human insulin degrading enzyme (IDE) plays a role in the proteolytic cleavage of insulin, glucagon, and other short, hydrophobic peptides with roles in glucose and cellular metabolism. Because of IDE’s role in insulin clearance, IDE inhibitors may hold promise as therapies for potentiating insulin signaling in patients suffering from type 2 diabetes mellitus. IDE is a large (~100 kDa) chambered protease of the conserved M16A subfamily of zinc metalloproteases. The enzyme adopts a structure that is analogous to a clamshell formed by the joining of the N terminal and C terminal domains. The characteristic zinc binding and catalytic motif (HXXEH) is positioned within the enzyme’s N terminus, while C terminal residues also play important roles in substrate binding and catalysis. Here, we describe the use of a computational work-flow for identifying novel IDE inhibitors. The work flow integrates mutation-based active site structural analysis, virtual screening, docking and fragment-based design. Initial computational results appear promising and should lead to assay testing in the near future