Abstract
Proteochemometric models of kinases derived from protein fields and ligand 4-point pharmacophoric fingerprints are predictive and visually interpretable.
Highlights
IntroductionKnown to modulate various cellular, metabolic and signaling pathways through phosphorylation.[1] Abnormalities in kinase regulation can lead to several diseases, including cancer, diabetes and inflammatory disorders, making kinases one of the most studied drug target classes
Protein kinases are enzymes, known to modulate various cellular, metabolic and signaling pathways through phosphorylation.[1]
We have shown that field-based proteochemometrics can be used successfully to generate both predictive and visually interpretable models, which is an advantage compared to models using simpler descriptions of target proteins
Summary
Known to modulate various cellular, metabolic and signaling pathways through phosphorylation.[1] Abnormalities in kinase regulation can lead to several diseases, including cancer, diabetes and inflammatory disorders, making kinases one of the most studied drug target classes. Thirty kinase inhibitors are currently available on the market.[2] The majority of these inhibitors targets the ATP binding sites, having a high probability for interacting with multiple kinases.[3] The similarity of the ATP binding pockets limits the selectivity of kinase inhibitors, often leading to toxic side effects. Better understanding of interactions between multiple ligands and multiple targets can support the design of novel kinase inhibitors with improved efficacy and selectivity
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