TY - JOUR A2 - GarcĂ­a-Sosa, Alfonso T. AU - Dixit, Anshuman AU - Verkhivker, Gennady M. PY - 2014 DA - 2014/04/08 TI - Structure-Functional Prediction and Analysis of Cancer Mutation Effects in Protein Kinases SP - 653487 VL - 2014 AB - 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 cancer mutations onto the conformational mobility 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 in kinases can also aid in the correlation of kinase mutation effects with clinical outcomes. SN - 1748-670X UR - https://doi.org/10.1155/2014/653487 DO - 10.1155/2014/653487 JF - Computational and Mathematical Methods in Medicine PB - Hindawi Publishing Corporation KW - ER -