Overcoming Analytical Challenges in Proximity Labeling Proteomics

Abstract

Proximity labeling (PL) proteomics has emerged as a powerful tool to capture both stable and transient protein interactions and subcellular networks. Despite the wide biological applications, PL still faces technical challenges in robustness, reproducibility, specificity, and sensitivity. Here, we discuss major analytical challenges in PL proteomics and highlight how the field is advancing to address these challenges by refining study design, tackling interferences, overcoming variation, developing novel tools, and establishing more robust platforms. We also provide our perspectives on best practices and the need for more robust, scalable, and quantitative PL technologies.