Protein–protein interactions (PPIs) drive cellular function. Obtaining quantitative maps of protein interactomes is essential for linking genotype to phenotype and predicting cellular outcomes. A large fraction of PPIs are mediated by domain–motif interactions (DMIs), where motifs within intrinsically disordered regions bind to structured domains in partner proteins. These transient and low-affinity interactions play central roles in regulatory and cell signaling processes, and their disruption has been linked to disease. However, due to their transient and dynamic nature, systematic experimental characterization of DMIs has been challenging. Recent advances in high-throughput experimental technologies and machine learning are transforming our ability to map and predict DMIs on a proteome-wide scale. Here, we review the molecular characteristics of motifs, domains, and their interactions; discuss emerging experimental and computational approaches for their discovery; and outline current challenges and future directions toward quantitative DMI interactomes.
Alvarado-Valverde et al. (Mon,) studied this question.