Interactomes

An interactome is the comprehensive map of molecular interactions within a cell, tissue, organism, or biological system. It focuses on how biomolecules—most notably proteins but also nucleic acids, metabolites, and other small molecules—physically or functionally interact to drive cellular processes. While many studies emphasize protein-protein interactions, interactomes can encompass various interaction types, including protein-DNA, protein-RNA, and metabolite-protein associations. Interactomes can be conceptualized as networks, with nodes representing molecules and edges representing interactions. These networks can be static representations or dynamic models that change across cell types, developmental stages, or disease states.

Mapping and analyzing interactomes rely on high-throughput experimental techniques and computational methods. Experimental approaches include yeast two-hybrid screens, affinity purification-mass spectrometry, cross-linking mass spectrometry, and proximity labeling. Computational inference integrates literature, omics data, and curated databases to predict and score interactions. Public resources such as BioGRID, IntAct, and STRING compile large-scale interaction data and provide network-visualization tools. Interactome data are often integrated with functional pathways to understand modular structure, hubs, and network communities.

Applications of interactome studies include elucidating cellular organization, signaling cascades, and protein complexes; interpreting disease mechanisms, identifying potential drug targets, and guiding systems biology models. Challenges include context specificity (cell type and condition), data quality and coverage, false positives and negatives, and integrating heterogeneous data into coherent networks. Despite these hurdles, interactome analysis remains central to understanding the coordinated molecular logic of life.