Efficient Identification of Novel Leads by Dynamic Focused Screening: PDK1 Case Study

Abstract

A dynamic, focused screening strategy that utilized a limited but diversified set of target-specific compounds was explored as an efficient means for the identification of inhibitors of the protein kinase PDK1. Approximately 21,500 compounds, including a 19,000 molecule kinase-focused compound collection (KFCC), were screened at two concentrations to identify initial leads. The KFCC included several empirically-derived, general kinase libraries and molecules chosen by PDK1-specific virtual screens. As was expected, this initial screen mostly identified potent leads with limited novelty. In order to overcome this limitation, the data from the screen were used to drive several rounds of a customized iterative focused screening (IFS) campaign. A machine-learning technique was used to build a predictive model to identify compounds to be screened in subsequent rounds. Molecules deemed not to be novel were removed from the training set for the next round, which allowed this campaign to progressively walk away from the chemical space covered by the KFCC. This resulted in the identification of PDK1 inhibitors which are uniquely different from publicly known chemotypes after just three rounds of screenings. A retrospective analysis of this IFS approach against an ultra-high throughput screen (uHTS) indicated that while uHTS is still the most prolific paradigm for lead identification, this dynamic, focused screening approach was successful in discovering novel scaffolds for a medicinal chemistry effort. Finally, a theoretical optimization suggested the dynamic, focused screening approaches could provide either a complementary or alternative approach to uHTS for the efficient and rapid lead identification.

Genetic and Pharmacological Inhibition of PDK1 in Cancer Cells

“…1). A parallel high throughput screening campaign (27,28) complemented our literature search, and seven small molecule inhibitors were selected for further profiling. In brief, compound 1 was identified from a focused kinase library screen using an AKT-derived peptide substrate and full-length PDK1 enzyme (27,28).…”

“…A parallel high throughput screening campaign (27,28) complemented our literature search, and seven small molecule inhibitors were selected for further profiling. In brief, compound 1 was identified from a focused kinase library screen using an AKT-derived peptide substrate and full-length PDK1 enzyme (27,28). It represents the tetracyclic class of pan-Janus kinase inhibitors (29,30), which we further optimized for selectivity, yielding the tricyclic class of PDK1 inhibitors exemplified by compound 2 (31).…”

Sensitive multiplexed analysis of kinase activities and activity-based kinase identification

“…To explore the potential of the single-reaction KAYAK strategy for use in drug discovery, we evaluated the activities of structurally diverse kinase inhibitors in cancer cell lines with deregulated PI3K pathway activity. Inhibitors were selected from the literature 22 and identified from a focused kinase library screen 23,24 to have affinity for PDK1 (Supplementary Fig. 12a).…”

Iterative Focused Screening with Biological Fingerprints Identifies Selective Asc-1 Inhibitors Distinct from Traditional High Throughput Screening

“…(13,15,16) In practice, however, this is usually not a feasible approach, and only 1-3 steps of expansion are performed. (13) Here, we built two models on the initial 45 K focused screen, and selected 7.5 K compounds with each model. For one model we used chemical descriptors (ECFP4 (17) ), and for the other model we used biological descriptors (HTS fingerprints (18) ).…”