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Cited by 15Protein Structure and DynamicsComputational Drug Discovery MethodsBioinformatics and Genomic Networks

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Protein Interaction Energy Landscapes are Shaped by Functional and also Non-functional Partners

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Schweke, Hugo, Mucchielli, Marie-Hélène, Sacquin-Mora, Sophie, Bei, Wanying, Lopes, Anne·2020·Journal of Molecular Biology
DOI 10.1016/j.jmb.2019.12.047

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Abstract

In the crowded cell, a strong selective pressure operates on the proteome to limit the competition between functional and non-functional protein-protein interactions. We developed an original theoretical framework in order to interrogate how this competition constrains the behavior of proteins with respect to their partners or random encounters. Our theoretical framework relies on a two-dimensional (2D) representation of interaction energy landscapes, with 2D energy maps, which reflect in a synthetic way the spatial distribution of the interaction propensity of a protein surface for another protein. We realized the interaction propensity mapping of proteins' surfaces in interaction with functional and arbitrary partners and asked whether the distribution of their interaction propensity is conserved during evolution. Therefore, we performed several thousands of cross-docking simulations to systematically characterize the energy landscapes of 103 proteins interacting with different sets of homologs, corresponding to their functional partner's family or arbitrary protein families. Then, we systematically compared the energy maps resulting from the docking of each protein with the different protein families of the dataset. Strikingly, we show that the interaction propensity not only of the binding sites but also of the rest of the surface is conserved for docking partners belonging to the same protein family. Interestingly, this observation holds for docked proteins corresponding to true but also arbitrary partners. Our theoretical framework enables the characterization of the energy behavior of a protein in interaction with hundreds of proteins and opens the way for the characterization of the behavior of proteins in a specific environment.

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Metadata

Authors
Schweke, H., Mucchielli, M.-H., Sacquin-Mora, S., Bei, W., & Lopes, A.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • Université Paris-Sud (FR)
Corresponding author
Lopes, Anne
ORCID
Venue
Journal of Molecular Biology
Publisher
Elsevier BV
Published
2020-02
Volume
432
Issue
4
Pages
1183-1198
ISSN
0022-2836 (ISSN-L)
DOI
10.1016/j.jmb.2019.12.047
OpenAlex
W3000093000
Cited by
15
References
5
Citations by year
2026: 1 · 2025: 2 · 2024: 2 · 2022: 5 · 2021: 3 · 2020: 1
FWCI
0.44
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Molecular Biology (acceptedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
Funders
Grand Équipement National De Calcul Intensif
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
protein-protein interaction, protein surface, protein families, binding sites, protein evolution, protein-protein docking
MeSH terms
Humans, Protein Binding, Protein Conformation, Proteins, Sequence Analysis, Protein, Protein Interaction Mapping, Databases, Protein, Molecular Docking Simulation

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