Abstract
Mutations in the BRCA1 gene are known to be a major cause of hereditary breast cancer. However, characterizing the point mutations associated with cancer in BRCA1 is challenging because the functional impact of most of them is still unknown. Nowadays, a variety of methods are employed to identify cancer-associated mutations in BRCA1. This study is aimed to assess the functional effects of two mutations, Asp1733Gly and Val1714Gly, using a combination of in silico tools and yeast functional transcription activator assay. Our computational analysis showed that theVal1714Gly mutation was deleterious, while the other one, Asp1733Gly, predicted as neutral. Also using yeast functional transcription activator assay, we found that the Asp1733Gly mutation displayed similar ability with positive controls. In contrast, the Val1714Gly mutation completely abrogated transcriptional activity in the yeast. These results suggested that Val1714Gly and Asp1733Gly can be classified as pathogenic and benign mutations for the BRCA1, respectively.