Scaffold-Based Analytics: Enabling Hit-to-Lead Decisions by Visualizing Chemical Series Linked across Large Datasets.

We present a method for visualizing and navigating large screening datasets while also taking into account their activities and properties. Our approach is to annotate the data with all possible scaffolds contained within each molecule. We have developed a Spotfire visualization, coupled to a fuzzy clustering approach based on the scaffold decomposition of the screening deck, used to drive the hit triage process. Progression decisions can be made using aggregate scaffold parameters and data from multiple datasets merged at the scaffold level. This visualization reveals overlaps that help prioritize hits, highlight tractable series, and posit ways to combine aspects of multiple hits. The structure-activity relationship of a large and complex hit is automatically mapped onto all constituent scaffolds making it possible to navigate, via any shared scaffold, to all related hits. This scaffold "walking" helps address bias toward a handful of potent and ligand-efficient molecules at the expense of coverage of chemical space. We consider two scaffold generation methods and explored their similarities and differences both qualitatively and quantitatively. The workflow of a Spotfire visualization used in combination with fuzzy clustering and structure annotation provides an intuitive view of large and diverse screening datasets. This allows teams to effortlessly navigate between structurally related molecules and enriches the population of leads considered and progressed in a manner complementary to established approaches.

Structure-based design of potent and selective 3-phosphoinositide-dependent kinase-1 (PDK1) inhibitors.

Phosphoinositide-dependent protein kinase-1(PDK1) is a master regulator of the AGC family of kinases and an integral component of the PI3K/AKT/mTOR pathway. As this pathway is among the most commonly deregulated across all cancers, a selective inhibitor of PDK1 might have utility as an anticancer agent. Herein we describe our lead optimization of compound 1 toward highly potent and selective PDK1 inhibitors via a structure-based design strategy. The most potent and selective inhibitors demonstrated submicromolar activity as measured by inhibition of phosphorylation of PDK1 substrates as well as antiproliferative activity against a subset of AML cell lines. In addition, reduction of phosphorylation of PDK1 substrates was demonstrated in vivo in mice bearing OCl-AML2 xenografts. These observations demonstrate the utility of these molecules as tools to further delineate the biology of PDK1 and the potential pharmacological uses of a PDK1 inhibitor.