PreprintCited by 16Protein 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·2018·Journal of Molecular Biology

Preprint — published as 10.1016/j.jmb.2019.12.047 · Paper page

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 that reflect in a synthetic way the propensity of a protein to interact with another protein. We investigated the propensity of protein surfaces to interact with functional and arbitrary partners and asked whether their interaction propensity is conserved during the evolution. Therefore, we performed several thousands of cross-docking simulations to systematically characterize the whole energy landscapes of 74 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 a given protein with the different protein families of the dataset. Strikingly, we show that the interaction propensity not only of the binding site but also of the rest of the protein surface is conserved for docking partners belonging to the same protein family. Interestingly, this observation holds for docked proteins corresponding to true but also to arbitrary partners. Our theoretical framework enables the characterization of the energy behavior of a protein in interaction with hundreds of selected partners and opens the way for further developments to study 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
Venue
Journal of Molecular Biology
Publisher
openRxiv
Published
2018-04-09
Volume
432
Issue
4
Pages
1183-1198
ISSN
0022-2836 (ISSN-L)
OpenAlex
W3000093000
Cited by
16
References
1
Citations by year
2026: 1 · 2025: 2 · 2024: 2 · 2022: 5 · 2021: 3 · 2020: 2 · 2019: 1
FWCI
0.53
Type
journal article
Language
en
Open access
Locations
  • Journal of Molecular Biology (acceptedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
Funders
  • Agence Nationale de la Recherche (ANR-11-LABX-0011)
  • Grand Équipement National De Calcul Intensif (DARI A0030707460)
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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