Summary Many tumors become addicted to autophagy for survival, suggesting inhibition of autophagy as a potential broadly-applicable cancer therapy. ULK1/Atg1 is the only serine/threonine kinase in the core autophagy pathway and thus represents an excellent drug target. Despite recent advances in the understanding of ULK1 activation by nutrient deprivation, how ULK1 promotes autophagy remains poorly understood. Here, we screened degenerate peptide libraries to deduce the optimal ULK1 substrate motif and discovered fifteen phosphorylation sites in core autophagy proteins that were verified as in vivo ULK1 targets. We utilized these ULK1 substrates to perform a cell-based screen to identify and characterize a potent ULK1 small molecule inhibitor. The compound SBI-0206965 is a highly selective ULK1 kinase inhibitor in vitro and suppressed ULK1-mediated phosphorylation events in cells, regulating autophagy and cell survival. SBI-0206965 greatly synergized with mTOR inhibitors to kill tumor cells, providing a strong rationale for their combined use in the clinic.

Three-component systems are often more complex than their two-component counterparts. Although the reversible association of three components in solution is critical for a vast array of chemical and biological processes, no general physical picture of such systems has emerged. Here we have developed a general, comprehensive framework for understanding ternary complex equilibria, which relates directly to familiar concepts such as “EC50” and “IC50” from simpler (binary complex) equilibria. Importantly, application of our model to data from the published literature has enabled us to achieve new insights into complex systems ranging from coagulation to therapeutic dosing regimens for monoclonal antibodies. We also provide an Excel spreadsheet to assist readers in both conceptualizing and applying our models. Overall, our analysis has the potential to render complex three-component systems – which have previously been characterized as “analytically intractable” – readily comprehensible to theoreticians and experimentalists alike.

SummaryCancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks.

Protein phosphorylation is the most common reversible post-translational modification in eukaryotes. Humans have over 500 protein kinases, of which more than a dozen are established targets for anticancer drugs. All kinases share a structurally similar catalytic domain, yet each one is uniquely positioned within signaling networks controlling essentially all aspects of cell behavior. Kinases are distinguished from one another based on their modes of regulation and their substrate repertoires. Coupling specific inputs to the proper signaling outputs requires that kinases phosphorylate a limited number of sites to the exclusion of hundreds of thousands of off-target phosphorylation sites. Here, we review recent progress in understanding mechanisms of kinase substrate specificity and how they function to shape cellular signaling networks.

SummaryProtein kinases control cellular responses to environmental cues by swift and accurate signal processing. Breakdowns in this high-fidelity capability are a driving force in cancer and other diseases. Thus, our limited understanding of which amino acids in the kinase domain encode substrate specificity, the so-called determinants of specificity (DoS), constitutes a major obstacle in cancer signaling. Here, we systematically discover several DoS and experimentally validate three of them, named the αC1, αC3, and APE-7 residues. We demonstrate that DoS form sparse networks of non-conserved residues spanning distant regions. Our results reveal a likely role for inter-residue allostery in specificity and an evolutionary decoupling of kinase activity and specificity, which appear loaded on independent groups of residues. Finally, we uncover similar properties driving SH2 domain specificity and demonstrate how the identification of DoS can be utilized to elucidate a greater understanding of the role of signaling networks in cancer (Creixell et al., 2015 [this issue of Cell]).