Using AI-predicted protein structures as a reference to predict loss-of-function activity in tumor suppressor breast cancer genes

The study reveals that generative AI protein predicted structures can outperform experimentally-derived structures in evaluating LOF activity from predicted protein stability in ordered regions of genes BRCA1, BRCA2, PALB2 and RAD51C. The study also highlights the predictive performance of AlphaMissense as the premier <i>in silico</i> missense prediction method to predict LOF activity from missense variants in these four tumor suppressor breast cancer genes. The code for this study can be downloaded for free on GitHub (https://github.com/rohandavidg/CarePred).