ArticleProceedings of the National Academy of Sciences of the United States of America2006
Free-energy distribution of binary protein-protein binding suggests cross-species interactome differences.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The universal statistical distributions of the affinity, equilibrium constants, kinetics and specificity in biomolecular recognition.PLoS computational biology · 2015Article
- Elucidating common structural features of human pathogenic variations using large-scale atomic-resolution protein networks.Human mutation · 2014Article
- Bayesian hierarchical models for protein networks in single-cell mass cytometry.Cancer informatics · 2014Review
- Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system.Microbiology and molecular biology reviews : MMBR · 2012Review
- Categorizing biases in high-confidence high-throughput protein-protein interaction data sets.Molecular & cellular proteomics : MCP · 2011Article
- Deducing topology of protein-protein interaction networks from experimentally measured sub-networks.BMC bioinformatics · 2008Article
- Constraints imposed by non-functional protein-protein interactions on gene expression and proteome size.Molecular systems biology · 2008Article
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4 authors.
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Abstract
Major advances in large-scale yeast two-hybrid screening have provided a global view of binary protein-protein interactions across species as dissimilar as human, yeast, and bacteria. Remarkably, these analyses have revealed that all species studied have a degree distribution of protein-protein binding that is approximately scale-free (varies as a power law) even though their evolutionary divergence times differ by billions of years. The universal power law shows only the surface of the rich information harbored by these high-throughput data. We develop a detailed mathematical model of the protein-protein interaction network based on association free energy, the biochemical quantity that determines protein-protein interaction strength. This model reproduces the degree distribution of all of the large-scale yeast two-hybrid data sets available and allows us to extract the distribution of free energy, the likelihood that a pair of proteins of a given species will bind. We find that across-species interactomes have significant differences that reflect the strengths of the protein-protein interaction. Our results identify a global evolutionary shift: more evolved organisms have weaker binary protein-protein binding. This result is consistent with the evolution of increased protein unfoldedness and challenges the dogma that only specific protein-protein interactions can be biologically functional.
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