The c-Jun N-terminal kinases (JNKs) are important mediators of cell viability and structural integrity in postmitotic neurons, which is required for maintaining synaptic connections and neural plasticity. In the present study, we chose differentiated PC12 cells as a well-characterised neuronal model system to selectively examine the regulation of basal JNK activity by extracellular signal-regulated kinase 1/2 (ERK1/2) and Akt. We detected a complex interaction between the kinases to prevent cell death and neurite loss. Especially the appropriate level of JNK activation determined cellular survival. Basal activity of ERK1/2 attenuated the potentiation of JNK phosphorylation and thereby the induction of apoptosis. Importantly, when JNK activity was too low, cell viability and the number of neurite-bearing cells also decreased, even though the activation of ERK1/2 was enhanced. In this case, the JNK-mediated survival signals via activating transcription factor-3 (ATF3) were inhibited. Furthermore, the phosphorylation of ERK1/2 induced by the JNK inhibitor SP600125 inhibited the basal activity of Akt, which normally supported cell viability. Thus, controlling JNK activity is crucial to promote survival and neurite stability of differentiated neuronal cells.
Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.