Evidence map›Paper›PMID 23590674›Full record

ArticleJournal of proteome research2013

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale.

Guray Kuzu, Attila Gursoy, Ruth Nussinov, Ozlem Keskin

Abstract read
In one paragraph

Article in Journal of proteome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Review
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  11. Review
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  13. CoDNaS 2.0: a comprehensive database of protein conformational diversity in the native state.Database : the journal of biological databases and curation · 2016
    Article
  14. Article
  15. Article
  16. Review
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  18. Article
  19. Modeling protein assemblies in the proteome.Molecular & cellular proteomics : MCP · 2014
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Guray KuzuCenter for Computational Biology and Bioinformatics and College of Engineering, Koc University Rumelifeneri Yolu, 34450 Sariyer Istanbul, Turkey.
Attila Gursoy
Ruth Nussinov
Ozlem Keskin

Funding

Biomolecular Recognition and Binding MechanismsZIABC010441 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$9.4M
Method Development: Efficient Computer Vision Based AlgorithmsZIABC010442 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$2.4M
CCR NIH HHS HHSN261200800001CIntramural NIH HHS ZIA BC010441NCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

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.

Indexed as

AlgorithmsMolecular Docking SimulationSoftwareDatabases, FactualDatabases, ProteinExtracellular Signal-Regulated MAP KinasesHumansProtein ConformationProtein Interaction MappingProteomeThermodynamicsExtracellular Signal-Regulated MAP KinasesProteome

Identifiers

PMID23590674
PMCPMC3685852

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.