Bridging structural biology and genomics: assessing protein interaction data with known complexes
Abstract
Currently, there is a major effort to map protein-protein interactions on a genome-wide scale. The utility of the resulting interaction networks will depend on the reliability of the experimental methods and the coverage of the approaches. Known macromolecular complexes provide a defined and objective set of protein interactions with which to compare biochemical and genetic data for validation. Here, we show that a significant fraction of the protein-protein interactions in genome-wide datasets, as well as many of the individual interactions reported in the literature, are inconsistent with the known 3D structures of three recent complexes (RNA polymerase II, Arp2/3 and the proteasome). Furthermore, comparison among genome-wide datasets, and between them and a larger (but less well resolved) group of 174 complexes, also shows marked inconsistencies. Finally, individual interaction datasets, being inherently noisy, are best used when integrated together, and we show how simple Bayesian approaches can combine them, significantly decreasing error rate.
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Y2H, APMS, and other high-throughput experimental approaches have identified many pairs of interacting proteins in yeast and other organisms, but there are discrepancies between sets generated using different methods and considerable false positive and false negative rates.
“Yeast two hybrid (Y2H), affinity-purification mass spectrometry (APMS), and other high-throughput experimental approaches have identified many pairs of interacting proteins in yeast and other organisms (1–5), but there are discrepancies between sets generated using the different methods and considerable false positive and false negative rates (6–8).”
From Computed structures of core eukaryotic protein complexes (2021) · cites this paper as [7]
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- Authors
- Edwards, A. M., Kus, B., Jansen, R., Greenbaum, D., Greenblatt, J., & Gerstein, M.
- Affiliations
- University of Toronto (CA)
- Yale University (US)
- Corresponding author
- Gerstein, Mark
- Venue
- Trends in Genetics
- Publisher
- Elsevier BV
- Published
- 2002-10
- Volume
- 18
- Issue
- 10
- Pages
- 529-536
- ISSN
- 0168-9525 (ISSN-L)
- OpenAlex
- W2134962976
- Cited by
- 276
- References
- 40
- Citations by year
- 2025: 3 · 2024: 5 · 2023: 2 · 2022: 1 · 2021: 3 · 2020: 3 · 2019: 2 · 2018: 5 · 2017: 3 · 2016: 7 · 2015: 16 · 2014: 16 · 2013: 12 · 2012: 17
- FWCI
- 1.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Trends in Genetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health
- Canadian Institutes of Health Research
- National Institute of General Medical Sciences (P50 GM 62413-01, P50GM062413)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- protein-protein interaction, protein-protein interaction network, macromolecular complexes, RNA polymerase II, Arp2/3 complex, proteasome, protein 3D structure, data integration
- MeSH terms
- Actins, Cysteine Endopeptidases, Multienzyme Complexes, Proteins, RNA Polymerase II, Two-Hybrid System Techniques, Genomics, Saccharomyces cerevisiae Proteins, Databases, Protein, Macromolecular Substances, Proteasome Endopeptidase Complex, Actin-Related Protein 3
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