Evidence map›Paper›PMID 23855673›Full record

ArticleProtein and peptide letters2014

MEGADOCK: an all-to-all protein-protein interaction prediction system using tertiary structure data.

Masahito Ohue, Yuri Matsuzaki, Nobuyuki Uchikoga, Takashi Ishida, Yutaka Akiyama

Abstract read
In one paragraph

Article in Protein and peptide letters, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Interactomics: Dissecting Protein Networks in Living Systems.Advances in experimental medicine and biology · 2026
    Review
  3. Article
  4. Epitope Mapping with Sidewinder: An XL-MS and Structural Modeling Approach.International journal of molecular sciences · 2025
    Article
  5. Review
  6. Review
  7. Docking Foundations: From Rigid to Flexible Docking.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Protein-protein interaction prediction with deep learning: A comprehensive review.Computational and structural biotechnology journal · 2022
    Review
  13. Tackling Dysfunction of Mitochondrial Bioenergetics in the Brain.International journal of molecular sciences · 2021
    Review
  14. Review
  15. Article
  16. Frontiers in genetics · 2020
    Article
  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

5 authors.

Masahito Ohue
Yuri Matsuzaki
Nobuyuki Uchikoga
Takashi Ishida
Yutaka AkiyamaGraduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 W8-76 Ookayama, Meguro-ku, Tokyo 152-8550, Japan. akiyama@cs.titech.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package "MEGADOCK" that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock.

Indexed as

SoftwareCluster AnalysisComputational BiologyFourier AnalysisModels, MolecularMolecular Docking SimulationProtein Interaction MappingProteinsProtein Structure, TertiaryStatic ElectricityTime FactorsProteins

Identifiers

PMID23855673
PMCPMC4443796

What OpenQuestion holds

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LicenceCC BY-NC
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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.