ArticleNature protocols2014
Affinity purification-mass spectrometry and network analysis to understand protein-protein interactions.
Article in Nature protocols, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers, 1 of them a synthesis that pooled it.
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Who cites it
109 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interactomics in plant defence: progress and opportunities.Molecular biology reports · 2023Pooled it
- Epitope Tagging and Coimmunoprecipitation to Identify Viral Protein Interactors.Methods in molecular biology (Clifton, N.J.) · 2027Article
- FAIMS-GPF XL-MS: crosslinking-mass spectrometry based on gas-phase fractionation.Nature communications · 2026Article
- A Brief Progress in Methods for Deciphering Protein-Protein Interaction Networks.International journal of molecular sciences · 2026Review
- Article
- MS-Based Proteomics Approach in Mapping Protein-Protein Interaction.Advances in experimental medicine and biology · 2026Review
- Proteomic analysis of the pyrenoid-traversing membranes of Chlamydomonas reinhardtii reveals novel components.The New phytologist · 2026Article
- A predicted structural interactome reveals binding interference from intrinsically disordered regions.PLoS computational biology · 2026Article
- Comprehensive Approaches to Protein Detection and Analysis in Mycobacterium tuberculosis.Advances in experimental medicine and biology · 2026Review
- A predicted structural interactome reveals binding interference from intrinsically disordered regions.bioRxiv : the preprint server for biology · 2025Article
- Mechanisms and Research Methods of Protein Modification in Virus Entry.Applied biochemistry and biotechnology · 2025Review
- Time-Resolved Analysis of Protein-Protein Ensembles Using a Destabilizing Domain to Map Dynamic Interactions of SARS-CoV-2 nsp15.ACS chemical biology · 2025Article
- Proteomic analysis of the pyrenoid-traversing membranes ofbioRxiv : the preprint server for biology · 2025Article
- Analysis of FAIMS for the study of affinity-purified protein complexes using the orbitrap ascend tribrid mass spectrometer.Molecular omics · 2025Article
- Discovery of an ApoE4-targeted small-molecule SirT1 enhancer for the treatment of Alzheimer's disease.Scientific reports · 2025Article
- Characterizing host-microbe interactions with bacterial effector proteins using proximity-dependent biotin identification (BioID).Communications biology · 2025Review
- Specific Monitoring the DNA Helicase Function via Anchor-Embedded DNA Probe.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Streptolysin O accelerates the conversion of plasminogen to plasmin.Nature communications · 2024Article
- Distinct Regions within SAP25 Recruit O-Linked Glycosylation, DNA Demethylation, and Ubiquitin Ligase and Hydrolase Activities to the Sin3/HDAC Complex.Journal of proteome research · 2024Article
- Article
49 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
Abstract
By determining protein-protein interactions in normal, diseased and infected cells, we can improve our understanding of cellular systems and their reaction to various perturbations. In this protocol, we discuss how to use data obtained in affinity purification-mass spectrometry (AP-MS) experiments to generate meaningful interaction networks and effective figures. We begin with an overview of common epitope tagging, expression and AP practices, followed by liquid chromatography-MS (LC-MS) data collection. We then provide a detailed procedure covering a pipeline approach to (i) pre-processing the data by filtering against contaminant lists such as the Contaminant Repository for Affinity Purification (CRAPome) and normalization using the spectral index (SIN) or normalized spectral abundance factor (NSAF); (ii) scoring via methods such as MiST, SAInt and CompPASS; and (iii) testing the resulting scores. Data formats familiar to MS practitioners are then transformed to those most useful for network-based analyses. The protocol also explores methods available in Cytoscape to visualize and analyze these types of interaction data. The scoring pipeline can take anywhere from 1 d to 1 week, depending on one's familiarity with the tools and data peculiarities. Similarly, the network analysis and visualization protocol in Cytoscape takes 2-4 h to complete with the provided sample data, but we recommend taking days or even weeks to explore one's data and find the right questions.
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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 OpenQuestion graph.