Structure-based functional analysis of BRCA1 RING domain variants: Concordance of computational mutagenesis, experimental assay, and clinical data

作     者：Masso, Majid Bansal, Anirudh Bansal, Arnav Henderson, Andrea 

作者机构：George Mason Univ Coll Sci Sch Syst Biol 10900 Univ Blvd MS 5B3 Manassas VA 20110 USA 

出 版 物：《BIOPHYSICAL CHEMISTRY》 (生物物理化学)

年 卷 期：2020年第266卷

页      面：106442-106442页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 07[理学] 0703[理学-化学] 

基　　金：George Mason University 

主　　题：Structure-function relationships Computational mutagenesis Variants Homology-directed DNA repair Machine learning Prediction 

摘      要：A significant impediment to the improvement of clinical outcomes in treating breast and ovarian cancers rests with the lack of available interpretations for BRCA1 variants of unknown significance. Two research groups recently implemented large-scale functional assays for quantifying effects of single missense mutations on homology-directed DNA repair activity of BRCA1 variants, which is critical for tumor suppression and strongly correlates with cancer risk, and their results are significantly concordant with each other as well as with known pathogenic and benign variant clinical data. In this work, we implemented an established computational mutagenesis procedure to characterize structural impacts of single residue replacements to the BRCA1 RING domain. The computational data showed similarly strong concordance with known clinical data as well as with experimental data from both functional assays. Predictions made by models trained on our computational data offer a complementary and orthogonal approach for classifying all remaining unexplored BRCA1 RING domain variants.