Proximity Labeling: An Empowering Tool for Deciphering Molecular Mechanisms

Abstract Proximity labeling (PL) has become a widely used approach for studying protein–protein interactions (PPIs) and addressing limitations of conventional techniques in capturing transient, weak interactions, and physiological protein networks within living systems. Over the past decade, core PL enzymes, notably APEX2, BirA* (BioID), and TurboID, have been iteratively engineered, with reported improvements in temporal resolution, targeting specificity, and biocompatibility. This review summarizes how PL technologies have developed and describes the enzymatic properties, catalytic mechanisms, and reported performance trade-offs of the commonly used tools. We then survey applications of PL in neuroscience, cardiology, oncology, and infectious disease, where it has been used to map compartment-specific proteomes and spatiotemporally regulated networks, including neural activity-driven PPIs, tumor microenvironment cross-talk, and host–pathogen interfaces. Many of the resulting candidates await orthogonal validation. We also describe recently reported conditional PL systems with optical, calcium- or oxygen-dependent control. Finally, we discuss open questions and possible directions for PL development, including enzyme-directed evolution, multisignal responsive regulation, cross-omics integration, and translational applications. This review is intended as a practical reference for researchers to support the selection and application of PL platforms in specific experimental contexts from mechanistic studies to the identification of candidate therapeutic targets.