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Updated: May 12, 2026

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
Published on: March 3, 2015
Bridging structural biology and genomics: assessing protein interaction data with known complexes.
Aled M Edwards1, Bart Kus, Ronald Jansen
1Banting and Best Dept of Medical Research, University of Toronto C.H. Best Institute, 112 College St, Toronto, Ontario M5G 1L6, Canada.
Genome-wide protein-protein interaction datasets contain errors inconsistent with known 3D structures. Integrating multiple noisy datasets using Bayesian methods improves accuracy and reliability of protein interaction networks.
Area of Science:
- Molecular Biology
- Structural Biology
- Bioinformatics
Background:
- Genome-wide studies aim to map protein-protein interactions (PPIs).
- The reliability and coverage of experimental methods are crucial for the utility of PPI networks.
- Known macromolecular complexes offer a benchmark for validating PPI data.
Purpose of the Study:
- To assess the consistency of genome-wide PPI datasets with known 3D structures.
- To evaluate the reliability of individual and integrated PPI data.
- To develop methods for improving the accuracy of PPI network construction.
Main Methods:
- Comparison of PPIs from genome-wide datasets against 3D structures of RNA polymerase II, Arp2/3, and the proteasome.
- Analysis of inconsistencies among different genome-wide PPI datasets.
- Evaluation of 174 additional macromolecular complexes.
- Application of Bayesian approaches to integrate multiple PPI datasets.
Main Results:
- A significant fraction of PPIs in genome-wide datasets and literature are inconsistent with known 3D structures.
- Marked inconsistencies exist among various genome-wide PPI datasets and with a larger set of complexes.
- Integrating individual, noisy PPI datasets using Bayesian methods significantly reduces the error rate.
Conclusions:
- Current genome-wide PPI data and literature-reported interactions exhibit structural inconsistencies.
- Independent PPI datasets are noisy and require integration for improved reliability.
- Bayesian integration offers a robust strategy to enhance the accuracy of protein interaction networks.
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