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Updated: Jan 10, 2026

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
Published on: August 21, 2019
IID 2025: Physical protein interaction data with detection types, co-purified protein sets, molecular docking, and
Max Kotlyar1, Chiara Pastrello1, Mark Abovsky1
1Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada.
None:
Biomedical research benefits from the rapid growth and diversity of experimentally detected protein-protein interactions (PPIs) by gaining important biological insights. However, increasingly dense PPI networks can be challenging to interpret and apply. The 2025 update of the Integrated Interactions Database (IID) enhances accessibility and utility through several new features. We identify and incorporate network structural components from co-purified protein sets, as well as curated and predicted complexes, enabling users to explore network organization beyond binary interactions. Functional, pathway, and disease associations of these components can be analyzed, enabling interactions to be grouped into higher-order structures with known or provisional biological roles. Users can now filter interactions by five detection types: pairwise, co-purification, colocalization, proximity, and other evidence. To extend the value and information of predicted interactions, we include interaction interface predictions for 53 647 PPIs, generated using the MEGADOCK docking algorithm, adding molecular detail for structural biology and variant impact studies. Finally, we map PPIs to 15 immune cell types and 12 additional normal tissues, offering tissue-specific views of interaction networks increasingly relevant in disease and immunology research. IID 2025 now includes over 1 million experimentally detected human PPIs, representing an 83% increase from the previous release, alongside expanded non-human networks. The portal remains publicly available at https://ophid.utoronto.ca/iid.
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