Abstract Protein–protein interactions (PPIs) are fundamental to virtually all biological processes. However, their highly dynamic and context-dependent nature poses significant challenges to traditional general network models in capturing their true biological significance. Here, we introduce the formation of context-specific PPI networks, emphasizing the importance of the biological context in which PPIs occur. We systematically compare traditional experimental methods, mass spectrometry (MS)-based high-throughput technologies, and structure- and biophysics-based approaches across six dimensions. Although these experimental methods have generated valuable data resources, they still suffer from limitations, including low capture efficiency for transient or weak interactions and a lack of gold-standard datasets with specific biological contexts. Furthermore, we review recent advances in context-specific PPI inference strategies centered on omics data integration, and highlight the emerging potential of large cellular models (LCMs) to generate context-aware representations that support the construction of context-specific PPI networks. In the future, comprehensive context-specific PPI networks are expected to more accurately reflect the biological system, thereby enabling deeper mechanistic insights, improving disease interpretation, and accelerating the discovery of therapeutic targets.
Nie et al. (Tue,) studied this question.