Evidence map›Paper›PMID 22559010›Full record

ArticleBMC biophysics2012

Arbitrary protein-protein docking targets biologically relevant interfaces.

Juliette Martin, Richard Lavery

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Article in BMC biophysics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
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  6. PEBP1/RKIP behavior: a mirror of actin-membrane organization.Cellular and molecular life sciences : CMLS · 2020
    Article
  7. Article
  8. Protein-protein binding supersites.PLoS computational biology · 2019
    Article
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  15. Inferring processes underlying B-cell repertoire diversity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015
    Article
  16. Article
  17. Quantifying selection in immune receptor repertoires.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  18. Review
  19. Article
4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Juliette MartinUniversité Lyon 1; CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux, IBCP, 7 passage du, Vercors, F-69367, France. Juliette.Martin@ibcp.fr.
Richard Lavery

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations.

resultsIn this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding protein), a kinase inhibitor with multiple partners.

conclusionsAn approach using arbitrary docking, and based solely on physical properties, can successfully identify biologically pertinent protein interfaces.

Identifiers

PMID22559010
PMCPMC3441232

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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.