Death by a thousand cuts through kinase inhibitor combinations that maximize selectivity and enable rational multitargeting
- Stony Brook University, United States
- Memorial Sloan Kettering Cancer Center, United States
- Goethe University Frankfurt, Germany
Abstract
Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicates the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.
Data availability
Instructions to run MMS, code, datasets, and MMS results are available at: https://github.com/iouthwaite/inhibitor_combinations
Article and author information
Author details
Funding
National Institutes of Health (R35GM119437)
- Markus A Seeliger
National Institutes of Health (T32GM136572)
- Ian R Outhwaite
National Institutes of Health (R01GM121505)
- John D Chodera
Damon Runyon Cancer Research Foundation (DRQ-14-22)
- Sukrit Singh
National Institutes of Health (T32GM008444)
- Ian R Outhwaite
Structural Genomics Consortium
- Stefan Knapp
German Translational Cancer Network
- Stefan Knapp
Deutsche Forschungsgemeinschaft (1399)
- Benedict-Tilman Berger
- Stefan Knapp
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, Outhwaite et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Death by a thousand cuts through kinase inhibitor combinations that maximize selectivity and enable rational multitargeting
eLife 12:e86189.
https://doi.org/10.7554/eLife.86189
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