错义突变
遗传学
生物
致病性
计算生物学
人口
基因
蛋白质组
背景(考古学)
基因组
突变
医学
微生物学
环境卫生
古生物学
作者
Jun Cheng,Guido Novati,Jinshan Pan,Clare Bycroft,Akvilė Žemgulytė,Taylor Applebaum,Alexander Pritzel,Lai Hong Wong,Michal Zielinski,Tobias Sargeant,Rosalia G. Schneider,Andrew Senior,John Jumper,Demis Hassabis,Pushmeet Kohli,Žiga Avsec
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:2023-09-19
卷期号:381 (6664)
被引量:437
标识
DOI:10.1126/science.adg7492
摘要
The vast majority of missense variants observed in the human genome are of unknown clinical significance. We present AlphaMissense, an adaptation of AlphaFold fine-tuned on human and primate variant population frequency databases to predict missense variant pathogenicity. By combining structural context and evolutionary conservation, our model achieves state-of-the-art results across a wide range of genetic and experimental benchmarks, all without explicitly training on such data. The average pathogenicity score of genes is also predictive for their cell essentiality, capable of identifying short essential genes that existing statistical approaches are underpowered to detect. As a resource to the community, we provide a database of predictions for all possible human single amino acid substitutions and classify 89% of missense variants as either likely benign or likely pathogenic.
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