|Anna Panchenko|| at 11:00
Deciphering the effect of cancer mutations on regulatory mechanisms of protein activity
Many signaling pathways involve a dense network of protein-protein interactions which are quite often disrupted in cancer. Mapping of cell signaling pathways with all elements and interactions will provide control and predictive power for the behavior of the system in response to perturbation and disease. Recently we designed a framework that allows consistent inference of protein interactions and binding sites by utilizing structural data on protein complexes. We use this framework to map and annotate the human protein interactome and analyze its properties. Since the structurally inferred interaction network provides the details of binding interfaces, we are able to estimate the effect of disease-associated point mutations on protein-protein binding and activity.
We have also analyzed an important element of cell signaling pathways, receptor tyrosine kinases (RTK), which can initiate the cascade of events implicated in cell division, cellular homeostasis and survival. Tyrosine kinases are very frequently mutated in cancer and the connection between cancer and kinase activation has been found fairly recently. In our study we attempt to link the stability of RTKs with their oncogenic potential and differential activity which can provide insights into the mechanisms of activation of different pathways by cancer mutations. We have analyzed both active and inactive states of kinase domains and find that inactive states are destabilized more than the active ones, which could lead to kinase activation. Moreover, a significant portion of cancer mutations come in doublets or triplets and their origin is not very well understood. According to our analysis multiple mutations in RTKs occur more often than expected by chance and may lead to selective advantages for the tumor cells. For many doublets we find a super-additive effect which points to the additional advantage of doublets for the tumor cell compared to singletons.