Abstract
The discovery of lead compounds relies on the iterative generation of structure-activity relationship data resulting from the synthesis and biological evaluation of hit analogues. Using traditional approaches, a significant time delay may occur from compound design to results, leading to slow and expensive hit-to-lead explorations. Herein, we have exploited the use of chemical toolboxes to expedite lead discovery and optimization. In particular, the integration of flow synthesizers, automation, process analytical technologies, and computational chemistry has provided a prototype system enabling the multicomponent flow synthesis, in-line analysis, and characterization of chiral tetracyclic quinolines as a novel class of PXR agonists. Within 29 compounds, a novel template 19b (3aS,11R,11aS) was identified with an EC(50) of 1.2 μM (efficacy 119%) at the PXR receptor.