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Binding Kinetics Survey of the Drugged Kinome Victoria Georgi, Felix Schiele, Benedict-Tilman Berger, Andreas Steffen, Paula A. Marin Zapata, Hans Briem, Stephan Menz, Cornelia Preuße, James D. Vasta, Matthew B. Robers, Michael Brands, Stefan Knapp, and Amaury E. Fernández-Montalván J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.8b08048 • Publication Date (Web): 26 Oct 2018 Downloaded from http://pubs.acs.org on October 26, 2018
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Journal of the American Chemical Society
Binding Kinetics Survey of the Drugged Kinome. Victoria Georgi1,2, Felix Schiele1,†, Benedict-Tilman Berger1,2,3, Andreas Steffen1, Paula A. Marin Zapata1, Hans Briem1, Stephan Menz1, Cornelia Preusse1, James D.Vasta4, Matthew B. Robers4, Michael Brands1, Stefan Knapp2,3 and Amaury Fernández-Montalván1, ‡,* 1
Bayer AG, Drug Discovery, Pharmaceuticals, Müllerstr. 178, 13353 Berlin, Germany. Structural Genomics Consortium, Institute for Pharmaceutical Chemistry, Johann Wolfgang Goethe-University, Max-vonLaue-Straße 9, 60438 Frankfurt am Main, Germany. 3 Structural Genomics Consortium, Buchmann Institute for Molecular Life Sciences, Johann Wolfgang Goethe-University, Max-von-Laue-Straße 15, 60438 Frankfurt am Main, Germany. 4 Promega Corporation, 2800 Woods Hollow Road, Fitchburg WI 53711, USA. 2
ABSTRACT: Target residence time is emerging as important optimization parameter in drug discovery, yet target and off-target engagement dynamics have not been clearly linked to the clinical performance of drugs. Here we developed high-throughput binding kinetics assays to characterize the interactions of 270 protein kinase inhibitors with 40 clinically relevant targets. Analysis of the results revealed that on-rates are better correlated with affinity than off-rates, and that the fraction of slowly dissociating drugtarget complexes increases from early/preclinical to late stage and FDA-approved compounds, suggesting distinct contributions by each parameter to clinical success. Combining binding parameters with PK/ADME properties, we illustrate in silico and in cells how kinetic selectivity could be exploited as an optimization strategy. Furthermore, using bio- and chemoinformatics we uncovered structural features influencing rate constants. Our results underscore the value of binding kinetics information in rational drug design, and provide a resource for future studies on this subject.
INTRODUCTION The discovery of new medicines is a lengthy and cost-intensive process with high attrition rates 1. Many drug candidates fail in clinical trials due to safety issues, often resulting from their interactions with proteins different from their primary biological targets (off-targets) 2,3. Kinase inhibitors (KIs) – one of the fastest growing class of therapeutic agents 4-6 – are not exempt from this problem 7-9. Today’s standard procedures for identifying compounds with potential off-target effects involve selectivity profiling in safety and in vitro pharmacology assay panels covering relevant target families 10. In the particular case of KIs, significant progress has been made with the development of biochemical and cellular assay technologies allowing kinome-wide characterization of inhibitor selectivity 11-14. While this approach has been effective for rationalizing adverse effects 8, equilibrium affinity measurements might overlook the dynamics of drug-target interactions in the context of open biological systems 15-17. The rates at which compounds bind and dissociate from their targets have long been proposed as key components to drug action 18 and many successful drugs are known to elicit their effects via non-equilibrium mechanisms 19. In recent years, the “drug target residence time” concept 15 initiated an ongoing debate about the
superiority of on- and off-rates over IC50’s per se as optimization parameter for candidate compounds 16,20-24. These discussions have triggered medicinal chemists’ interest on the molecular determinants for binding kinetics (BK) properties 25-33, and the term structure kinetics relationships (SKR) has been coined to describe studies aiming at the identification of structural elements influencing BK 26,27. Coincidentally, one of these papers focused on inhibitors of the kinase CDK8, and more publications investigating KIs from a BK viewpoint have followed ever since 28-30. To date, most studies addressing BK in drug discovery have focused on small numbers of targets and ligands, with a few notable exceptions relying on heterogeneous datasets from the literature 22,23,34,35. Here we used high throughput methods recently developed in our laboratory 36 to characterize the BK properties of 270 KIs interacting with 40 clinically relevant kinases. The generated array of drug binding rate constants is the largest measured so far under similar experimental conditions. To illustrate its potential applications, we used this dataset to feed and validate pharmacometrics models and to perform bio- and chemoinformatics analyses. The results provide insights for the prospective design of compounds with specific BK properties leading to improved safety and efficacy profiles. RESULTS Large scale binding kinetics profiling of compounds targeting the human kinome. Owing to the specific scope of this study, we focused on clinically validated kinases (i.e. targeted by marketed drugs). Thus, with the exceptions of the lipid kinase PI3KA and some serine threonine kinases (STKs) being currently pursued in preclinical and clinical studies, our assay panel is mostly populated by receptor tyrosine kinases (RTKs) (Fig. 1a and Table S1). This choice is reflected by the distance matrices of the kinase constructs clustered by sequence similarity (Fig. S1a). Based on our previous work on CDK2 36, we established a standardized workflow for the development of equilibrium- and kinetic probe competition assays (ePCA and kPCA) suitable for STKs,
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Journal of the American Chemical Society
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