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PubMed Central
Article . 2025
License: CC BY NC ND
Data sources: PubMed Central
Journal of Visualized Experiments
Article . 2025 . Peer-reviewed
Data sources: Crossref
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Mapping Dysfunctional Protein-Protein Interactions in Disease

Authors: Rodina, Anna; Erdjument-Bromage, Hediye; Monetti, Mara; Li, Zhuoning; Chakrabarty, Souparna; Wang, Shujuan; Digwal, Chander S.; +6 Authors

Mapping Dysfunctional Protein-Protein Interactions in Disease

Abstract

Protein-protein interaction (PPI) networks are dynamically remodeled in disease, yet most systems biology approaches focus on changes in protein abundance, overlooking critical interaction-level dysfunction. Here, we present a robust, chemoproteomic method-dysfunctional Protein-Protein Interactome (dfPPI)-that enables high-throughput, systematic, disease-contextual mapping of PPI network dysfunctions in cells and primary human tissue. This method integrates chemical biology probes that selectively capture epichaperome-based interactome assemblies with label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) and network-based computational analysis, to uncover the rewiring of protein networks not apparent from transcriptomic or proteomic data alone. The dfPPI platform can be applied across disease states, species, and tissues to identify actionable nodes of dysfunction and enable high-resolution, systems-level insights into disease progression. In this protocol, we demonstrate step-by-step procedures for sample preparation, chemical probe treatment, affinity enrichment, label-free LC-MS/MS analysis, and bioinformatics workflows used to generate and interpret dfPPI datasets. This article aims to promote reproducibility and accessibility of this approach, supporting its adoption by the broader systems biology and translational research communities.

Related Organizations
Keywords

Proteomics, Tandem Mass Spectrometry, Protein Interaction Mapping, Humans, Article, Chromatography, Liquid

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green