Evidence map›Paper›PMID 25488330›Full record

ArticleProteins2015

Structural templates for comparative protein docking.

Ivan Anishchenko, Petras J Kundrotas, Alexander V Tuzikov, Ilya A Vakser

Abstract readComparative Study
In one paragraph

Article in Proteins, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Structural motifs in protein cores and at protein-protein interfaces are different.Protein science : a publication of the Protein Society · 2021
    Article
  4. Article
  5. Protein Docking Model Evaluation by Graph Neural Networks.Frontiers in molecular biosciences · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Dockground: A comprehensive data resource for modeling of protein complexes.Protein science : a publication of the Protein Society · 2018
    Article
  15. SnapDock-template-based docking by Geometric Hashing.Bioinformatics (Oxford, England) · 2017
    Article
  16. Article
  17. Article
  18. 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.

Ivan AnishchenkoCenter for Bioinformatics, The University of Kansas, Lawrence, Kansas, 66047.
Petras J KundrotasCenter for Bioinformatics, The University of Kansas, Lawrence, Kansas, 66047.
Alexander V TuzikovUnited Institute of Informatics Problems, National Academy of Sciences, Minsk, 220012, Belarus.
Ilya A VakserCenter for Bioinformatics, The University of Kansas, Lawrence, Kansas, 66047.

Funding

Integrated Resource for Protein Recognition StudiesR01GM074255 · NIGMS · UNIVERSITY OF KANSAS LAWRENCE · PI VAKSER, ILYA · 2005 to 2024
$6.2M
NIGMS NIH HHS R01 GM074255NIGMS NIH HHS R01GM074255
6 · The paper itself

Abstract

Structural characterization of protein-protein interactions is important for understanding life processes. Because of the inherent limitations of experimental techniques, such characterization requires computational approaches. Along with the traditional protein-protein docking (free search for a match between two proteins), comparative (template-based) modeling of protein-protein complexes has been gaining popularity. Its development puts an emphasis on full and partial structural similarity between the target protein monomers and the protein-protein complexes previously determined by experimental techniques (templates). The template-based docking relies on the quality and diversity of the template set. We present a carefully curated, nonredundant library of templates containing 4950 full structures of binary complexes and 5936 protein-protein interfaces extracted from the full structures at 12 Å distance cut-off. Redundancy in the libraries was removed by clustering the PDB structures based on structural similarity. The value of the clustering threshold was determined from the analysis of the clusters and the docking performance on a benchmark set. High structural quality of the interfaces in the template and validation sets was achieved by automated procedures and manual curation. The library is included in the Dockground resource for molecular recognition studies at http://dockground.bioinformatics.ku.edu.

Indexed as

Molecular Docking SimulationProtein Structure, TertiaryBinding SitesCluster AnalysisComputational BiologyCrystallography, X-RayDatabases, ProteinInternetProtein BindingProtein Interaction MappingProteinsReproducibility of ResultsProteinsbenchmark setsprotein interactionsprotein modelingprotein recognitionstructure prediction

Identifiers

PMID25488330
PMCPMC4461561

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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.