Evidence map›Paper›PMID 31874620›Full record

ArticleBMC bioinformatics2019

Pushing the accuracy limit of shape complementarity for protein-protein docking.

Yumeng Yan, Sheng-You Huang

Abstract read
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Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

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18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. HDOCK update for modeling protein-RNA/DNA complex structures.Protein science : a publication of the Protein Society · 2022
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Docking approaches for modeling multi-molecular assemblies.Current opinion in structural biology · 2020
    Review
  15. Review
  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

2 authors.

Yumeng YanSchool of Physics, Huazhong University of Science and Technology, Luoyu Road 1037, Wuhan, Hubei, 430074, P.R. China.
Sheng-You HuangSchool of Physics, Huazhong University of Science and Technology, Luoyu Road 1037, Wuhan, Hubei, 430074, P.R. China. huangsy@hust.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein-protein docking is a valuable computational approach for investigating protein-protein interactions. Shape complementarity is the most basic component of a scoring function and plays an important role in protein-protein docking. Despite significant progresses, shape representation remains an open question in the development of protein-protein docking algorithms, especially for grid-based docking approaches.

resultsWe have proposed a new pairwise shape-based scoring function (LSC) for protein-protein docking which adopts an exponential form to take into account long-range interactions between protein atoms. The LSC scoring function was incorporated into our FFT-based docking program and evaluated for both bound and unbound docking on the protein docking benchmark 4.0. It was shown that our LSC achieved a significantly better performance than four other similar docking methods, ZDOCK 2.1, MolFit/G, GRAMM, and FTDock/G, in both success rate and number of hits. When considering the top 10 predictions, LSC obtained a success rate of 51.71% and 6.82% for bound and unbound docking, respectively, compared to 42.61% and 4.55% for the second-best program ZDOCK 2.1. LSC also yielded an average of 8.38 and 3.94 hits per complex in the top 1000 predictions for bound and unbound docking, respectively, followed by 6.38 and 2.96 hits for the second-best ZDOCK 2.1.

conclusionsThe present LSC method will not only provide an initial-stage docking approach for post-docking processes but also have a general implementation for accurate representation of other energy terms on grids in protein-protein docking. The software has been implemented in our HDOCK web server at http://hdock.phys.hust.edu.cn/.

Indexed as

AlgorithmsMolecular Docking SimulationProtein BindingProteinsSoftwareProteinsFast-Fourier transformMolecular dockingProtein-protein InteractionsScoring functionShape complementarity

Identifiers

PMID31874620
PMCPMC6929408

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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.