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滑窗交互语法 (SWING):用于和蛋白相互作用的通用交互语言模型

Jane C Siwek^1,2,3,4, Alisa A Omelchenko^1,2,3,4, Prabal Chhibbar^1,2,5

¹Center for Systems immunology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

|July 28, 2025

概括

我们开发了滑窗交互语法 (SWING),一种交互语言模型 (iLM),用于预测蛋白质交互. SWING准确地预测了主要基因相容性复杂相互作用和变异效应,优于现有方法.

科学领域:

计算生物学是一种计算生物学.
生物信息学是一种生物信息学.
蛋白质科学是一种蛋白质科学.

背景情况:

蛋白质语言模型对于序列嵌入至关重要,但在相互作用预测方面存在困难.
了解蛋白质-蛋白质相互作用对于生物和疾病研究至关重要.

研究的目的:

开发一种用于预测蛋白质相互作用的新型相互作用语言模型 (iLM).
为了利用氨基酸性质,为专业的蛋白质相互作用词汇.
评估模型对MHC类I和II相互作用和变异效应的性能.

主要方法:

开发了一个iLM架构的滑动窗口交互语法 (SWING).
利用氨基酸性质的差异来创建一个交互词汇.
应用SWING来预测主要基因相容性复合体 (pMHC) 类I和II相互作用.
评估了SWING能够预测变体中断相互作用和MHC类之间的交叉预测的能力.

主要成果:

SWING成功地预测了pMHC类I和II相互作用.
第I类SWING模型展示了对II类相互作用的独特交叉预测能力.
SWING准确地预测了与自身免疫性疾病风险等位基因相关的小鼠pMHCII类相互作用.
该模型准确地预测了序列变异如何破坏蛋白质-蛋白质相互作用.

结论:

SWING是一种可泛化,零射击的iLM,有效地学习蛋白质-蛋白质相互作用的语言.
在交互预测方面,SWING的性能优于被动蛋白语言模型的嵌入.
开发的iLM架构提供了一个有价值的工具,仅从序列数据预测蛋白质相互作用中断.

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