MPIDNN-GPPI:多蛋白语言模型,具有改进的深度神经网络,用于概括蛋白质-蛋白质相互作用预测
Yane Li1, Chengfeng Wang1, Haibo Gu1
1College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou, 311300, China.
BMC genomics
|November 19, 2025
概括
本研究介绍了MPIDNN-GPPI,这是一个新的深度学习框架,用于使用蛋白质语言模型预测蛋白质-蛋白质相互作用 (PPI). 该模型展示了强大的跨物种预测能力,优于现有方法.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 预测蛋白质与蛋白质相互作用 (PPI) 对于理解生物过程至关重要.
- 实验性PPI识别是昂贵和耗时的.
- 计算方法,特别是深度学习,提供了高效的替代方案,但在一般化,强度和稳定性方面存在困难,特别是在数据有限的物种中.
研究的目的:
- 开发一种新的,基于序列的蛋白质-蛋白质相互作用 (PPI) 预测框架 (MPIDNN-GPPI),具有增强的概括性和稳定性.
- 利用蛋白质语言模型 (PLM) 来进行特征提取和深度神经网络 (DNN) 来进行相互作用预测.
- 提高PPI计算预测的准确性和稳定性,特别是在不同物种之间.
主要方法:
- 利用两个蛋白质语言模型,Ankh和ESM-2,来生成蛋白质序列嵌入.
- 使用深度神经网络 (DNN) 来学习PLM生成的特征向量的表示.
- 集成了一个多头注意力机制,以捕捉远程依赖关系,并将它们与DNN表示进行融合,以评估相互作用概率.
主要成果:
- 在各种物种中,MPIDNN-GPPI实现了高AUC值,证明了强大的跨物种预测性能 (例如,在H. sapiens上训练和M. musculus上测试时,0.959 AUC).
- 结合Ankh和ESM-2嵌入式的模型优于使用单个PLM的模型.
- 与单独DNN相比,包括多头注意力的显著提高了性能,证实了该模型的概括能力.
结论:
- MPIDNN-GPPI对跨物种PPI预测具有显著的概括能力.
- 拟议的框架有效地预测PPI,即使在单一物种的数据上进行训练.
- 这种方法为PPI预测在各种生物环境中提供了更有效,更准确的解决方案.
相关概念视频
02:04Protein-protein Interfaces
14.4K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
14.4K
02:04Protein-Protein Interfaces
4.4K
4.4K
02:26Protein Networks
4.4K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.4K
02:26Protein Networks
2.7K
2.7K
01:57Protein Complexes with Interchangeable Parts
2.8K
Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
2.8K
01:57Protein Complexes with Interchangeable Parts
2.1K
2.1K