Exploiting polypharmacology for drug target deconvolution.
Polypharmacology (action of drugs against multiple targets) represents a tempting avenue for new drug development; unfortunately, methods capable of exploiting the known polypharmacology of drugs for target deconvolution are lacking. Here, we present an ensemble approach using elastic net regularization combined with mRNA expression profiling and previously characterized data on a large set of kinase inhibitors to identify kinases that are important for epithelial and mesenchymal cell migration. By profiling a selected optimal set of 32 kinase inhibitors in a panel against six cell lines, we identified cell type-specific kinases that regulate cell migration. Our discovery of several informative kinases with a previously uncharacterized role in cell migration (such as Mst and Taok family of MAPK kinases in mesenchymal cells) may represent novel targets that warrant further investigation. Target deconvolution using our ensemble approach has the potential to aid in the rational design of more potent but less toxic drug combinations.
['Gujral|Taranjit Singh|TS|', 'Peshkin|Leonid|L|', 'Kirschner|Marc W|MW|']
D002460:Cell Line D002465:Cell Movement D016503:Drug Delivery Systems D055808:Drug Discovery D006801:Humans D008648:Mesoderm D010641:Phenotype D064798:Polypharmacology D047428:Protein Kinase Inhibitors D011505:Protein-Tyrosine Kinases D015203:Reproducibility of Results
cancer cell migration perturbation biology predictive modeling regularized regression systems pharmacology