A genome-wide RNAi screen identifies potential drug targets in a C. elegans model of α1-antitrypsin deficiency.

α1-Antitrypsin deficiency (ATD) is a common genetic disorder that can lead to end-stage liver and lung disease. Although liver transplantation remains the only therapy currently available, manipulation of the proteostasis network (PN) by small molecule therapeutics offers great promise. To accelerate the drug-discovery process for this disease, we first developed a semi-automated high-throughput/content-genome-wide RNAi screen to identify PN modifiers affecting the accumulation of the α1-antitrypsin Z mutant (ATZ) in a Caenorhabditis elegans model of ATD. We identified 104 PN modifiers, and these genes were used in a computational strategy to identify human ortholog-ligand pairs. Based on rigorous selection criteria, we identified four FDA-approved drugs directed against four different PN targets that decreased the accumulation of ATZ in C. elegans. We also tested one of the compounds in a mammalian cell line with similar results. This methodology also proved useful in confirming drug targets in vivo, and predicting the success of combination therapy. We propose that small animal models of genetic disorders combined with genome-wide RNAi screening and computational methods can be used to rapidly, economically and strategically prime the preclinical discovery pipeline for rare and neglected diseases with limited therapeutic options.

An analog of glibenclamide selectively enhances autophagic degradation of misfolded α1-antitrypsin Z.

The classical form of α1-antitrypsin deficiency (ATD) is characterized by intracellular accumulation of the misfolded variant α1-antitrypsin Z (ATZ) and severe liver disease in some of the affected individuals. In this study, we investigated the possibility of discovering novel therapeutic agents that would reduce ATZ accumulation by interrogating a C. elegans model of ATD with high-content genome-wide RNAi screening and computational systems pharmacology strategies. The RNAi screening was utilized to identify genes that modify the intracellular accumulation of ATZ and a novel computational pipeline was developed to make high confidence predictions on repurposable drugs. This approach identified glibenclamide (GLB), a sulfonylurea drug that has been used broadly in clinical medicine as an oral hypoglycemic agent. Here we show that GLB promotes autophagic degradation of misfolded ATZ in mammalian cell line models of ATD. Furthermore, an analog of GLB reduces hepatic ATZ accumulation and hepatic fibrosis in a mouse model in vivo without affecting blood glucose or insulin levels. These results provide support for a drug discovery strategy using simple organisms as human disease models combined with genetic and computational screening methods. They also show that GLB and/or at least one of its analogs can be immediately tested to arrest the progression of human ATD liver disease.