Using Bioluminescent Kinase Profiling Strips to Identify Kinase Inhibitor Selectivity and Promiscuity

Non-linear Deep Neural Network for Rapid and Accurate Prediction of Phenotypic Responses to Kinase Inhibitors

Protein kinase inhibitors are one of the most successful targeted therapies to date. Despite this progress, additional kinase inhibitors are needed to expand the target space as well as overcome drug resistance that has emerged in clinical setting. Here, we developed KiDNN (Kinase inhibitor prediction using Deep Neural Networks). KiDNN utilizes non-linear, multilayer feedforward network that mimics complex and dynamic kinase-driven signaling pathways. We used KiDNN to predict the effect of ∼200 kinase inhibitors on migration of breast and liver cancer cells. We show that the prediction accuracy of KiDNN outperformed other prediction tools based on linear models. We validated that an inhibitor of tyrosine kinase receptors, and an inhibitor of Src family kinases, decreased migration of triple-negative breast cancer cells, consistent with the role of these kinases in driving motility. Overall, we show that non-linear, DNN-based models provide a powerful approach to in silico screen hundreds of kinase inhibitors.

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Deep Neural Networks mimic non-linear, complex intracellular signaling pathways

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Multi-phase grid search identified best networks with less computation time

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Prediction accuracy of KiDNN outperformed linear models

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KiDNN can accelerate drug discovery and development efforts

A Flexible Workflow for Automated Bioluminescent Kinase Selectivity Profiling

Kinase profiling during drug discovery is a necessary process to confirm inhibitor selectivity and assess off-target activities. However, cost and logistical limitations prevent profiling activities from being performed in-house. We describe the development of an automated and flexible kinase profiling workflow that combines ready-to-use kinase enzymes and substrates in convenient eight-tube strips, a bench-top liquid handling device, ADP-Glo Kinase Assay (Promega, Madison, WI) technology to quantify enzyme activity, and a multimode detection instrument. Automated methods were developed for kinase reactions and quantification reactions to be assembled on a Gilson (Middleton, WI) PIPETMAX, following standardized plate layouts for single- and multidose compound profiling. Pipetting protocols were customized at runtime based on user-provided information, including compound number, increment for compound titrations, and number of kinase families to use. After the automated liquid handling procedures, a GloMax Discover (Promega) microplate reader preloaded with SMART protocols was used for luminescence detection and automatic data analysis. The functionality of the automated workflow was evaluated with several compound-kinase combinations in single-dose or dose-response profiling formats. Known target-specific inhibitions were confirmed. Novel small molecule-kinase interactions, including off-target inhibitions, were identified and confirmed in secondary studies. By adopting this streamlined profiling process, researchers can quickly and efficiently profile compounds of interest on site.

Bioluminescent kinase strips: A novel approach to targeted and flexible kinase inhibitor profiling

In addition to target efficacy, drug safety is a major requirement during the drug discovery process and is influenced by target specificity. Therefore, it is imperative that every new drug candidate be profiled against various liability panels that include protein kinases. Here, an effective methodology to streamline kinase inhibitor profiling is described. An accessible standardized profiling system for 112 protein kinases covering all branches of the kinome was developed. This approach consists of creating different sets of kinases and their corresponding substrates in multi-tube strips. The kinase stocks are pre-standardized for optimal kinase activity and used for inhibitor profiling using a bioluminescent ADP detection assay. We show that these strips can routinely generate inhibitor selectivity profiles for small or broad kinase family panels. Lipid kinases were also assembled in strip format and profiled together with protein kinases. We identified two specific PI3K inhibitors that have off-target effects on CK2 that were not reported before and would have been missed if compounds were not profiled against lipid and protein kinases simultaneously. To validate the accuracy of the data generated by this method, we confirmed that the inhibition potencies observed are consistent with published values produced by more complex technologies such as radioactivity assays.