Emergence of power-law distributions in protein-protein interaction networks through study bias
- University of Erlangen-Nuremberg, Germany
- European Institute of Oncology, Italy
- Technische Universität Braunschweig, Germany
- Technical University of Munich, Germany
Abstract
Degree distributions in protein-protein interaction (PPI) networks are believed to follow a power law (PL). However, technical and study bias affect the experimental procedures for detecting PPIs. For instance, cancer-associated proteins have received disproportional attention. Moreover, bait proteins in large-scale experiments tend to have many false-positive interaction partners. Studying the degree distributions of thousands of PPI networks of controlled provenance, we address the question if PL distributions in observed PPI networks could be explained by these biases alone. Our findings are supported by mathematical models and extensive simulations and indicate that study bias and technical bias suffice to produce the observed PL distribution. It is, hence, problematic to derive hypotheses about the topology of the true biological interactome from the PL distributions in observed PPI networks. Our study casts doubt on the use of the PL property of biological networks as a modeling assumption or quality criterion in network biology.
Data availability
We analyzed only previously published data for this work. To facilitate reproducibility, we deposited the used datasets at https://zenodo.org/record/8288898.
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Emergence of power law distributions in protein-protein interaction networks through study biasZenodo, https://doi.org/10.5281/zenodo.7695120.
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intact.txtIntAct Molecular Interaction Database, 10.1093/nar/gkt1115.
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HIPPIE v2.2HIPPIE Human Integrated Protein-Protein Interaction rEference.
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UniProtUniProt, 10.1093/nar/gkac1052.
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Table_S1_gene_info_at_protein_level.xlsxGTEx, 10.1016/j.cell.2020.08.036.
Article and author information
Author details
David B Blumenthal
Funding
Bundesministerium für Bildung und Forschung (031L0309A)
- David B Blumenthal
Klaus Tschira Stiftung (00.003.2024)
- David B Blumenthal
- Markus List
- Martin H Schaefer
Fondazione AIRC per la ricerca sul cancro ETS (MFAG 21791)
- Martin H Schaefer
Fondazione AIRC per la ricerca sul cancro ETS (Bridge Grant n. 29162)
- Martin H Schaefer
Ministero della Salute (Ricerca Corrente)
- Martin H Schaefer
Ministero della Salute (5x1000 funds)
- Martin H Schaefer
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2024, Blumenthal et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Emergence of power-law distributions in protein-protein interaction networks through study bias
eLife 13:e99951.
https://doi.org/10.7554/eLife.99951
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