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Updated: Aug 17, 2026

In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces
Published on: March 19, 2010
Going high-throughput: Dynamic conformations and interactions in vivo
Zhou Gong1, Qun Zhao2, Min Sun1
1State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China.
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Proteins are intrinsically dynamic molecules that continuously explore conformational ensembles to execute biological functions. Conventional structural biology methods rely on in vitro reconstitution of purified components and therefore capture predominantly static snapshots, often overlooking the regulatory roles of the cellular microenvironment, such as molecular crowding, weak interaction networks, and post-translational modifications. This limitation has driven an urgent need to transition from in vitro reconstruction to in vivo characterization within living cells. Nuclear magnetic resonance (NMR) spectroscopy provides atomic-resolution insights into structure and motions spanning multiple timescales, yet its application is constrained by molecular weight limits, isotopic labeling requirements, and inherently low throughput. Cross-linking mass spectrometry (XL-MS) complements NMR by delivering sparse but long-range spatial restraints without an upper molecular weight limit. The integration of NMR and XL-MS establishes a powerful synergistic framework that bridges atomic-resolution local structures and large-scale interaction topologies, thereby enabling comprehensive characterization of protein dynamic conformations and interaction networks in native environments. Here, we review how this integrative strategy advances the understanding of intrinsically disordered proteins, multi-domain proteins, and dynamic protein-protein interaction networks in native cellular environments. We further discuss emerging technological frontiers, including hyperpolarized NMR, photo-cross-linking, organelle-resolved analysis, and artificial intelligence-guided integrative modeling, which together promise to transform our ability to resolve the true functional states of proteins inside cells.
