Structural and functional impact of cancer-related missense somatic mutations.

ABSTRACT: A number of large-scale cancer somatic genome sequencing projects are now identifying genetic alterations in cancers. Evaluation of the effects of these mutations is essential for understanding their contribution to tumorigenesis. We have used SNPs3D, a software suite originally developed for analyzing nonsynonymous germ-line variants, to identify single-base mutations with a high impact on protein structure and function. Two machine learning methods are used: one identifying mutations that destabilize protein three-dimensional structure and the other utilizing sequence conservation and detecting all types of effects on in vivo protein function. Incorporation of detailed structure information into the analysis allows detailed interpretation of the functional effects of mutations in specifi

SUBMITTER: Shi Z 

PROVIDER: S-EPMC4177034 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature