ArticleComputational and structural biotechnology journal2024
Using AI-predicted protein structures as a reference to predict loss-of-function activity in tumor suppressor breast cancer genes.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The loss-of-function (LOF) classification of most missense variants in tumor suppressor breast cancer genes Results: Complex AlphaFold2 structures of the BRCA1-C terminal (BRCT) domain and the DNA-binding (DB) domain of Conclusions: 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
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