Activity-based protein profiling (ABPP) has been used extensively to discover and optimize selective inhibitors of enzymes. Here, we show that ABPP can also be implemented to identify the converse-small-molecule enzyme activators. Using a kinetically controlled, fluorescence polarization-ABPP assay, we identify compounds that stimulate the activity of LYPLAL1-a poorly characterized serine hydrolase with complex genetic links to human metabolic traits. We apply ABPP-guided medicinal chemistry to advance a lead into a selective LYPLAL1 activator suitable for use in vivo. Structural simulations coupled to mutational, biochemical and biophysical analyses indicate that this compound increases LYPLAL1's catalytic activity likely by enhancing the efficiency of the catalytic triad charge-relay system. Treatment with this LYPLAL1 activator confers beneficial effects in a mouse model of diet-induced obesity. These findings reveal a new mode of pharmacological regulation for this large enzyme family and suggest that ABPP may aid discovery of activators for additional enzyme classes.
Phenotypic screening is making a comeback in drug discovery as the maturation of chemical proteomics methods has facilitated target identification for bioactive small molecules. A limitation of these approaches is that time-consuming genetic methods or other means are often required to determine the biologically relevant target (or targets) from among multiple protein-compound interactions that are typically detected. Here, we have combined phenotypic screening of a directed small-molecule library with competitive activity-based protein profiling to map and functionally characterize the targets of screening hits. Using this approach, we identify carboxylesterase 3 (Ces3, also known as Ces1d) as a primary molecular target of bioactive compounds that promote lipid storage in adipocytes. We further show that Ces3 activity is markedly elevated during adipocyte differentiation. Treatment of two mouse models of obesity-diabetes with a Ces3 inhibitor ameliorates multiple features of metabolic syndrome, illustrating the power of the described strategy to accelerate the identification and pharmacologic validation of new therapeutic targets.
