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Abstract：
Identifying pathogenic variants and underlying functional alterations is challenging. To this end, we introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions over existing methods, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. Whilst its prioritization performance is state-of-the-art, a distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific aspects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the identification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neurodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism-driven studies of human inherited disease have the potential to significantly accelerate the discovery of clinically actionable variants.
摘要：
鉴定致病变体和潜在的功能改变是具有挑战性的。为此,我们介绍了MutPred2，一种改进致病性氨基酸取代优先于现有方法的工具，产生潜在致病的分子机制，并返回个体基因组上可解释的致病性得分分布。虽然它的优先性能是最先进的，MutPred2的一个显著特征是变异对蛋白质结构和功能特定方面的影响的概率建模,可用于指导表型改变变异的实验研究.我们证明了MutPred2在鉴定与孟德尔疾病相关的结构和功能突变特征以及与复杂神经发育疾病相关的从头突变的优先级方面的实用性。然后，我们通过实验验证了在患有此类疾病的患者中鉴定出的几种变体的功能影响。我们认为，机制驱动的人类遗传性疾病的研究有可能显着加速发现临床可操作的变异。
