Search for: All records

Abstract Background Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential response shown by altered kinases to drug treatment in patients and cell-based assays. However, an incomplete understanding of the relationships connecting genome, proteome and drug sensitivity profiles present a major bottleneck in targeting kinases for personalized medicine. Results In this study, we propose a multi-component Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model and neural networks framework for providing explainable models of protein kinase inhibition and drug response ( $$\hbox {IC}_{50}$$ IC 50 ) profiles in cell lines. Using non-small cell lung cancer as a case study, we show that interaction terms that capture associations between drugs, pathways, and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib). In particular, protein–protein interactions associated with the JNK apoptotic pathway, associations between lung development and axon extension, and interaction terms connecting drug substructures and the volume/charge of mutant residues at specific structural locations contribute significantly to the observed $$\hbox {IC}_{50}$$ IC 50 values in cell-based assays. Conclusions By integrating multi-omics data in the QSMART model, we not only predict drug responses in cancer cell lines with high accuracy but also identify features and explainable interaction terms contributing to the accuracy. Although we have tested our multi-component explainable framework on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles. 

Aberrant regulation of metabolic kinases by altered redox homeostasis substantially contributes to aging and various diseases, such as diabetes. We found that the catalytic activity of a conserved family of fructosamine-3-kinases (FN3Ks), which are evolutionarily related to eukaryotic protein kinases, is regulated by redox-sensitive cysteine residues in the kinase domain. The crystal structure of the FN3K homolog fromArabidopsis thalianarevealed that it forms an unexpected strand-exchange dimer in which the ATP-binding P-loop and adjoining β strands are swapped between two chains in the dimer. This dimeric configuration is characterized by strained interchain disulfide bonds that stabilize the P-loop in an extended conformation. Mutational analysis and solution studies confirmed that the strained disulfides function as redox “switches” to reversibly regulate the activity and dimerization of FN3K. Human FN3K, which contains an equivalent P-loop Cys, was also redox sensitive, whereas ancestral bacterial FN3K homologs, which lack a P-loop Cys, were not. Furthermore, CRISPR-mediated knockout of FN3K in human liver cancer cells altered the abundance of redox metabolites, including an increase in glutathione. We propose that redox regulation evolved in FN3K homologs in response to changing cellular redox conditions. Our findings provide insights into the origin and evolution of redox regulation in the protein kinase superfamily and may open new avenues for targeting human FN3K in diabetic complications.