Evidence map›Paper›PMID 31199455›Full record

ArticleBioinformatics (Oxford, England)2020

iScore: a novel graph kernel-based function for scoring protein-protein docking models.

Cunliang Geng, Yong Jung, Nicolas Renaud, Vasant Honavar, Alexandre M J J Bonvin, Li C Xue

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

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0cells of the map it votes in
39citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

The trial behind it

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3 · Its place in the literature

Who cites it

39 citing papers in PubMed.

  1. Article
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  5. Simplicity within biological complexity.Bioinformatics advances · 2025
    Article
  6. Article
  7. ZEPPI: Proteome-scale sequence-based evaluation of protein-protein interaction models.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  8. Review
  9. Article
  10. Open-Source Machine Learning in Computational Chemistry.Journal of chemical information and modeling · 2023
    Review
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Cunliang GengBijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht 3584 CH, The Netherlands.
Yong JungBioinformatics & Genomics Graduate Program, Pennsylvania State University, University Park, PA 16802, USA.
Nicolas RenaudNetherlands eScience Center, Amsterdam 1098 XG, The Netherlands.
Vasant HonavarBioinformatics & Genomics Graduate Program, Pennsylvania State University, University Park, PA 16802, USA.
Alexandre M J J BonvinBijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht 3584 CH, The Netherlands.
Li C XueBijvoet Center for Biomolecular Research, Faculty of Science - Chemistry, Utrecht University, Utrecht 3584 CH, The Netherlands.

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Penn State Clinical and Translational Science InstituteUL1TR000127 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI SINOWAY, LAWRENCE I · 2012 to 2015
$17.1M
NCATS NIH HHS UL1 TR000127NCATS NIH HHS UL1 TR002014
6 · The paper itself

Abstract

motivationProtein complexes play critical roles in many aspects of biological functions. Three-dimensional (3D) structures of protein complexes are critical for gaining insights into structural bases of interactions and their roles in the biomolecular pathways that orchestrate key cellular processes. Because of the expense and effort associated with experimental determinations of 3D protein complex structures, computational docking has evolved as a valuable tool to predict 3D structures of biomolecular complexes. Despite recent progress, reliably distinguishing near-native docking conformations from a large number of candidate conformations, the so-called scoring problem, remains a major challenge.

resultsHere we present iScore, a novel approach to scoring docked conformations that combines HADDOCK energy terms with a score obtained using a graph representation of the protein-protein interfaces and a measure of evolutionary conservation. It achieves a scoring performance competitive with, or superior to, that of state-of-the-art scoring functions on two independent datasets: (i) Docking software-specific models and (ii) the CAPRI score set generated by a wide variety of docking approaches (i.e. docking software-non-specific). iScore ranks among the top scoring approaches on the CAPRI score set (13 targets) when compared with the 37 scoring groups in CAPRI. The results demonstrate the utility of combining evolutionary, topological and energetic information for scoring docked conformations. This work represents the first successful demonstration of graph kernels to protein interfaces for effective discrimination of near-native and non-native conformations of protein complexes. AVAILABILITY AND IMPLEMENTATION: The iScore code is freely available from Github: https://github.com/DeepRank/iScore (DOI: 10.5281/zenodo.2630567). And the docking models used are available from SBGrid: https://data.sbgrid.org/dataset/684). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

AlgorithmsComputational BiologyMolecular Docking SimulationProteinsProtein BindingProtein ConformationSoftwareProteins

Identifiers

PMID31199455
PMCPMC6956772

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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.