Exploiting Conformational Ensembles in Modeling Protein–Protein Interactions on the Proteome Scale
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Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than "blind" docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited an ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested "difficult" cases in a docking-benchmark data set, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26 to 66%, and 57% of the interactions were successfully predicted in an "unbiased" scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome scale. We constructed the structural network of ERK interacting proteins as a case study.
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Using experimentally known protein conformational ensembles in proteome-scale modeling of protein-protein interactions boosts successful prediction from ~26% to 66%.
“Using experimentally known protein conformational ensembles in modeling protein-protein interactions on the proteome scale can boost the percentage of successfully predicted interactions from ~26 to 66%.478”
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 [478]
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Chasovskikh, N. Y., Bobrysheva, A. A., & Chizhik, E. E. (2024) · Vavilov Journal of Genetics and Breeding · doi:10.18699/vjgb-24-38
- Authors
- Kuzu, G., Gursoy, A., Nussinov, R., & Keskin, O.
- Affiliations
- Koç University (TR)
- Center for Computational Biology and Bioinformatics and College of Engineering, Koc University Rumelifeneri Yolu, 34450 Sariyer Istanbul, Turkey
- Tel Aviv University (IL)
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-04-30
- Volume
- 12
- Issue
- 6
- Pages
- 2641-2653
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- PMC
- PMC3685852
- OpenAlex
- W2074382324
- Cited by
- 47
- References
- 84
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 1 · 2022: 4 · 2021: 1 · 2020: 4 · 2018: 5 · 2017: 4 · 2016: 8 · 2015: 2 · 2014: 9 · 2013: 5
- FWCI
- 3.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Proteome Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (HHSN261200800001C)
- National Cancer Institute (HHSN261200800001E), ZIABC010441)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- protein-protein interaction prediction, conformational ensembles, knowledge-based scoring, PRISM, Protein Data Bank, docking benchmark, structural networks
- MeSH terms
- Algorithms, Humans, Protein Conformation, Software, Thermodynamics, Databases, Factual, Proteome, Protein Interaction Mapping, Databases, Protein, Extracellular Signal-Regulated MAP Kinases, Molecular Docking Simulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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