Machines vs. Ensembles: Effective MAPK Signaling through Heterogeneous Sets of Protein Complexes
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Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively will ultimately shape how we conceptualize the function, evolution and engineering of signaling networks.
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A conventional mechanical description of protein complexes requiring well-defined quaternary structures is misleading because signaling and regulatory complexes are highly dynamic ensembles.
“Since signaling and other regulatory complexes typically consist of highly dynamic molecular ensembles a ‘conventional’ mechanical description of protein complexes that requires well-defined quaternary structures is misleading.534–535”
From Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell (2016) · cites this paper as [535]
Ensembles can signal effectively at the cellular systems level through a multiple-conformations combinatorial scheme representing weak linkage.
“The results illustrated on the cellular systems level that ensembles are able to signal effectively through a multiple-conformations combinatorial scheme that represents a form of weak linkage.”
From Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell (2016) · cites this paper as [535]
A hierarchical assembly model for scaffold-based signaling machines could not replicate experimental observations.
“In contrast, the model that employs hierarchical assembly pathways to produce scaffold-based signaling machines could not replicate experimental observations.”
From Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell (2016) · cites this paper as [535]
An ensemble model of yeast pheromone signaling generated reliable responses matching experimental observations.
“They found that the ensemble model generated reliable responses that match experimental observations.”
From Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell (2016) · cites this paper as [535]
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- Authors
- Suderman, R., & Deeds, E. J.
- Affiliations
- University of Kansas (US)
- Corresponding author
- Deeds, Eric J.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-10-10
- Volume
- 9
- Issue
- 10
- Pages
- e1003278
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC3794900
- OpenAlex
- W2006466539
- Cited by
- 52
- References
- 62
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 8 · 2018: 6 · 2017: 12 · 2016: 8 · 2015: 4 · 2014: 3
- FWCI
- 2.24
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- KU ScholarWorks (University of Kansas) (submittedVersion, cc-by)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
- Keywords
- MAPK signaling, protein complexes, rule-based models, scaffold proteins, hierarchical assembly, network plasticity
- MeSH terms
- Computer Simulation, Models, Biological, Pheromones, Saccharomyces cerevisiae, Least-Squares Analysis, MAP Kinase Signaling System, Saccharomyces cerevisiae Proteins, Intracellular Signaling Peptides and Proteins, Systems Biology
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