研究人员报道了AlphaMissense，它是AlphaFold在人类和灵长类变异群体频率数据库基础上进行微调的改良版，用于预测错义变异的致病性。通过将结构背景和演化保守相结合，这个模型在广泛的遗传和实验基准中取得了最先进的结果，而这一切都不需要在此类数据上进行明确的训练。
基因的平均致病性得分还能预测其细胞本质，从而识别出现有统计方法无法检测到的短小本质基因。作为一项社区资源，研究人员提供了一个预测人类所有可能的单氨基酸置换的数据库，并将89%的错义变异分类为可能良性或可能致病。
据悉，在人类基因组中观察到的绝大多数错义变异的临床意义不明。
附：英文原文
Title: Accurate proteome-wide missense variant effect prediction with AlphaMissense
Author: Jun Cheng, Guido Novati, Joshua Pan, Clare Bycroft, Akvil emgulyt, Taylor Applebaum, Alexander Pritzel, Lai Hong Wong, Michal Zielinski, Tobias Sargeant, Rosalia G. Schneider, Andrew W. Senior, John Jumper, Demis Hassabis, Pushmeet Kohli, iga Avsec
Issue&Volume: 2023-09-19
Abstract: 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.
DOI: adg7492
Source: https://www.science.org/doi/10.1126/science.adg7492