title: Structure-functional prediction and analysis of cancer mutation effects in protein kinases.
abstract: 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.
authors.affiliation: Department of Pharmaceutical Chemistry, School of Pharmacy, The University of Kansas, 2010 Becker Drive, Lawrence, KS 66047, USA ; Department of Biotechnology, Institute of Life Sciences, Bhubaneswar, India.
authors.forename: Anshuman
authors.initials: A
authors.lastname: Dixit
authors.affiliation: School of Computational Sciences and Crean School of Health and Life Sciences, Schmid College of Science and Technology, Chapman University, One University Drive, Orange, CA 92866, USA ; Department of Pharmacology, University of California San Diego, La Jolla, CA, USA.
authors.forename: Gennady M
authors.initials: GM
authors.lastname: Verkhivker
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D006801:Humans; D008958:Models, Molecular; D009154:Mutation; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism; D020641:Polymorphism, Single Nucleotide; D011494:Protein Kinases / Q000235:genetics*; D012984:Software
chemical_list: D011494:Protein Kinases