Research Article Structure-Functional Prediction and Analysis of Cancer Mutation Effects in Protein Kinases

Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A central goal of cancer research is to discover and characterize the functional effects of mutated genes that contribute to tumorigenesis. In this study, we provide a detailed structural classification and analysis of functional dynamics for members of protein kinase families that are known to harbor cancer mutations. We also present a systematic computational analysis that combines sequence and structure-based prediction models to characterize the effect of cancer mutations in protein kinases. We focus on the differential effects of activating point mutations that increase protein kinase activity and kinase-inactivating mutations that decrease activity.Mapping of cancermutations onto the conformationalmobility profiles of known crystal structures demonstrated that activating mutations could reduce a steric barrier for the movement from the basal “low ” activity state to the “active ” state. According to our analysis, the mechanism of activating mutations reflects a combined effect of partial destabilization of the kinase in its inactive state and a concomitant stabilization of its active-like form, which is likely to drive tumorigenesis at some level. Ultimately, the analysis of the evolutionary and structural features of the major cancer-causing mutational hotspot i