Evidence map›Paper›PMID 28200016›Full record

ArticleBioinformatics (Oxford, England)2017

IRaPPA: information retrieval based integration of biophysical models for protein assembly selection.

Iain H Moal, Didier Barradas-Bautista, Brian Jiménez-García, Mieczyslaw Torchala, Arjan van der Velde, Thom Vreven, Zhiping Weng, Paul A Bates, Juan Fernández-Recio

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants.Protein science : a publication of the Protein Society · 2022
    Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Improved cluster ranking in protein-protein docking using a regression approach.Computational and structural biotechnology journal · 2021
    Article
  13. Docking approaches for modeling multi-molecular assemblies.Current opinion in structural biology · 2020
    Review
  14. Article
  15. Article
  16. What method to use for protein-protein docking?Current opinion in structural biology · 2019
    Review
  17. Article
  18. Article
  19. 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

9 authors.

Iain H MoalEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
Didier Barradas-BautistaLife Science Department, Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain.
Brian Jiménez-GarcíaLife Science Department, Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain.
Mieczyslaw TorchalaBiomolecular Modelling Laboratory, The Francis Crick Institute, London, UK.
Arjan van der VeldeProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA.
Thom VrevenProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA.
Zhiping WengProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA.
Paul A BatesBiomolecular Modelling Laboratory, The Francis Crick Institute, London, UK.
Juan Fernández-RecioLife Science Department, Joint BSC-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain.

Funding

Template-based docking refinement approach to protein-protein structure modelingR01GM116960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2016 to 2019
$1.4M
Biotechnology and Biological Sciences Research Council BB/N011600/1Cancer Research UK 10748Cancer Research UK A10748NIGMS NIH HHS R01 GM116960Wellcome Trust FC001003
6 · The paper itself

Abstract

motivationIn order to function, proteins frequently bind to one another and form 3D assemblies. Knowledge of the atomic details of these structures helps our understanding of how proteins work together, how mutations can lead to disease, and facilitates the designing of drugs which prevent or mimic the interaction.

resultsAtomic modeling of protein-protein interactions requires the selection of near-native structures from a set of docked poses based on their calculable properties. By considering this as an information retrieval problem, we have adapted methods developed for Internet search ranking and electoral voting into IRaPPA, a pipeline integrating biophysical properties. The approach enhances the identification of near-native structures when applied to four docking methods, resulting in a near-native appearing in the top 10 solutions for up to 50% of complexes benchmarked, and up to 70% in the top 100. AVAILABILITY AND IMPLEMENTATION: IRaPPA has been implemented in the SwarmDock server ( http://bmm.crick.ac.uk/∼SwarmDock/ ), pyDock server ( http://life.bsc.es/pid/pydockrescoring/ ) and ZDOCK server ( http://zdock.umassmed.edu/ ), with code available on request. CONTACT: moal@ebi.ac.uk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Molecular Docking SimulationProtein ConformationSoftwareInformation Storage and RetrievalInternetProtein Interaction Mapping

Identifiers

PMID28200016
PMCPMC5783285

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.