ArticleNature methods2024
DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 23 citations in OpenAlex.
- Complex assembly and activity states as multifaceted protein attributes explaining phenotypic variability.Molecular systems biology · 2026Article
- PCIPG: A comprehensive framework for protein complex identification based on a probabilistic graphical model.PLoS computational biology · 2026Article
- Proteomic investigation of signaling dynamics: from static maps to network rewiring.Bioscience reports · 2026Review
- Five tenets for advancing evidence-based precision medicine.Nature medicine · 2026Review
- A tissue-specific atlas of protein-protein associations enables prioritization of candidate disease genes.Nature biotechnology · 2026Article
- ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning.Nature communications · 2026Article
- A guide to building the matrisome interactome: from computational predictions to experimental validation.The FEBS journal · 2026Review
- Characterization of WAC interactions with R2TP and TTT chaperone complexes linking glucose and glutamine availability to mTORC1 activity.FEBS open bio · 2025Article
- Understanding the molecular diversity of synapses.Nature reviews. Neuroscience · 2025Review
- Knowledge Landscape and Hotspots of Research in Transthyretin Amyloid Cardiomyopathy: A Bibliometric Analysis.International journal of medical sciences · 2025Article
- Introducing dysfunctional Protein-Protein Interactome (dfPPI) - A platform for systems-level protein-protein interaction (PPI) dysfunction investigation in disease.Current opinion in structural biology · 2024Review
- Mass Spectrometry-Based Proteomics Technologies to Define Endogenous Protein-Protein Interactions and Their Applications to Cancer and Viral Infectious Diseases.Mass spectrometry reviewsReview
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 3 countries.
Funding
Abstract
Most proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing most cellular processes. Affinity purification of the protein of interest combined with liquid chromatography coupled to tandem mass spectrometry (AP-MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can, however, not be resolved from a single AP-MS experiment but requires computational inference from multiple time- and resource-intensive reciprocal AP-MS experiments. Here we introduce deep interactome profiling by mass spectrometry (DIP-MS), which combines AP with blue-native-PAGE separation, data-independent acquisition with mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organization of the human prefoldin family of complexes, resolving distinct prefoldin holo- and subcomplex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.