使用从蛋白质语言模型中嵌入的零射击细分可以识别人类蛋白质组中的功能区域
Ami G Sangster1, Cameron Dufault2, Haoning Qu1
1Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada.
PLoS computational biology
|November 11, 2025
概括
我们介绍了零射击蛋白质细分 (ZPS),一种使用蛋白质语言模型嵌入的方法来识别和分类蛋白质细分. 在没有事先培训的情况下,ZPS在预测功能单位 (如域和无序区域) 方面表现优于现有的工具.
科学领域:
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
- 蛋白质科学 蛋白质科学
背景情况:
- 蛋白质的功能是由不同的单元决定的,如折叠的域和内在无序的区域.
- 从序列中识别和分类这些部分对于自动蛋白质注释至关重要.
- 现有的方法通常依赖于保存的序列模式.
研究的目的:
- 介绍零射击蛋白质细分 (ZPS),一种使用无监督蛋白质语言模型嵌入的新方法来识别和分类蛋白质细分.
- 为了证明ZPS能够在不依赖于保存序列模式或不需要训练的情况下细分蛋白质的能力.
- 评估ZPS的表现与已建立的生物信息学工具相比,以及其发现新功能区域的能力.
主要方法:
- 使用了来自无监督蛋白质语言模型ProtT5.5的嵌入.
- 开发了零射击蛋白质细分 (ZPS) 来预测蛋白质细分边界,而不需要参数训练或微调.
- 将ZPS应用于人类蛋白质组,并分析细分嵌入物以进行分类.
主要成果:
- 人类蛋白质组的ZPS边界预测在复制UniProt注释方面显示出高精度的准确性,与已建立的工具相比.
- ZPS 段的 ProtT5 嵌入成功分类了超过 200 个常见的 UniProt 注释,包括域和内在无序的区域.
- 介绍了蛋白质嵌入的新型可视化方法,有助于解释不同的功能单元.
结论:
- ZPS提供了一种强大的,公正的方法来识别和分类已知和未注释的蛋白质部分.
- 该方法成功地在内在无序的区域内识别了未注释的线粒体向信号和子类域.
- 对蛋白质段嵌入的分析具有显著的潜力,可以揭示对蛋白质功能的新见解,特别是对于无序和不太了解的区域.
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