Strategies for constructing context-specific protein-protein interaction networks.

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.