Kinome-Wide Profiling Prediction of Small Molecules

5 years ago

Kinome-Wide Profiling Prediction of Small Molecules

Benjamin Merget, Simone Fulle, Frieda A. Sorgenfrei

Extensive kinase profiling data, covering more than half of the human kinome, are available nowadays and allow the construction of activity prediction models of high practical utility. Proteochemometric (PCM) approaches use compound and protein descriptors, which enables the extrapolation of bioactivity values to thus far unexplored kinases. In this study, the potential of PCM to make large-scale predictions on the entire kinome is explored, considering the applicability on novel compounds and kinases, including clinically relevant mutants. A rigorous validation indicates high predictive power on left-out kinases and superiority over individual kinase QSAR models for new compounds. Furthermore, external validation on clinically relevant mutant kinases reveals an excellent predictive power for mutations spread across the ATP binding site. Kinome-wide prediction of kinase inhibitors: The capabilities of proteochemometric (PCM) models to make large-scale predictions on the entire kinome was explored. The combination of a compound fingerprint with a protein fingerprint 1) improves the activity prediction for each kinase relative to individually trained models and 2) enables prediction of the activity of compounds for the entire kinome, including cancer-related resistance mutations.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/cmdc.201700180