Advancements in the interpretation of variants of unknown significance are critical for improving clinical outcomes. In a recent study, massive parallel assays were used to experimentally quantify the effects of missense substitutions in the RING domain of BRCA1 on E3 ubiquitin ligase activity as well as BARD1 RING domain binding. These attributes were subsequently used for training a predictive model of homology-directed DNA repair levels for these BRCA1 variants relative to wild type, which is critical for tumor suppression. Here, relative structural changes characterizing BRCA1 variants were quantified by using an efficient and cost-free computational mutagenesis technique, and we show that these features lead to improvements in model performance. This work underscores the potential for bench researchers to gain valuable insights from computational tools, prior to implementing costly and time-consuming experiments.

中文翻译：

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BRCA1 RING 域变体的功能分析：计算得出的结构数据可以改进用于训练预测模型的实验特征

解释意义不明的变异的进展对于改善临床结果至关重要。在最近的一项研究中，大规模平行分析用于实验量化 BRCA1 的 RING 域中的错义替换对 E3 泛素连接酶活性以及 BARD1 RING 域结合的影响。这些属性随后用于训练这些 BRCA1 变体相对于野生型的同源导向 DNA 修复水平的预测模型，这对于抑制肿瘤至关重要。在这里，表征 BRCA1 变体的相对结构变化通过使用高效且免费的计算诱变技术进行量化，我们表明这些特征导致模型性能的提高。