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Article

Decoys for Docking

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Alan P. Graves,†‡ Ruth Brenk,† and Brian K. Shoichet*†
Department of Pharmaceutical Chemistry, Graduate Group in Biophysics, University of California San Francisco, 1700 4th Street, San Francisco, California 94143-2550
J. Med. Chem., 2005, 48 (11), pp 3714–3728
DOI: 10.1021/jm0491187
Publication Date (Web): May 7, 2005
Copyright © 2005 American Chemical Society
CASSection:
Pharmacology

Abstract

Abstract Image

Molecular docking is widely used to predict novel lead compounds for drug discovery. Success depends on the quality of the docking scoring function, among other factors. An imperfect scoring function can mislead by predicting incorrect ligand geometries or by selecting nonbinding molecules over true ligands. These false-positive hits may be considered “decoys”. Although these decoys are frustrating, they potentially provide important tests for a docking algorithm; the more subtle the decoy, the more rigorous the test. Indeed, decoy databases have been used to improve protein structure prediction algorithms and protein−protein docking algorithms. Here, we describe 20 geometric decoys in five enzymes and 166 “hit list” decoysi.e., molecules predicted to bind by our docking program that were tested and found not to do sofor β-lactamase and two cavity sites in lysozyme. Especially in the cavity sites, which are very simple, these decoys highlight particular weaknesses in our scoring function. We also consider the performance of five other widely used docking scoring functions against our geometric and hit list decoys. Intriguingly, whereas many of these other scoring functions performed better on the geometric decoys, they typically performed worse on the hit list decoys, often highly ranking molecules that seemed to poorly complement the model sites. Several of these “hits” from the other scoring functions were tested experimentally and found, in fact, to be decoys. Collectively, these decoys provide a tool for the development and improvement of molecular docking scoring functions. Such improvements may, in turn, be rapidly tested experimentally against these and related experimental systems, which are well-behaved in assays and for structure determination.

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Citing Articles

View all 34 citing articles

Citation data is made available by participants in CrossRef's Cited-by Linking service. For a more comprehensive list of citations to this article, users are encouraged to perform a search in SciFinder.

This article has been cited by 18 ACS Journal articles (5 most recent appear below).

  • Cover Image

    Cheminformatics Meets Molecular Mechanics: A Combined Application of Knowledge-Based Pose Scoring and Physical Force Field-Based Hit Scoring Functions Improves the Accuracy of Structure-Based Virtual Screening

    Jui-Hua Hsieh, Shuangye Yin, Xiang S. Wang, Shubin Liu, Nikolay V. Dokholyan, and Alexander Tropsha
    Journal of Chemical Information and Modeling2012 52 (1), 16-28
    • Cheminformatics Meets Molecular Mechanics: A Combined Application of Knowledge-Based Pose Scoring and Physical Force Field-Based Hit Scoring Functions Improves the Accuracy of Structure-Based Virtual Screening

      Jui-Hua Hsieh, Shuangye Yin, Xiang S. Wang, Shubin Liu, Nikolay V. Dokholyan, and Alexander Tropsha
      Journal of Chemical Information and Modeling2012 52 (1), 16-28

      Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening (VS), which is most frequently manifested in the scoring functions’ inability to discriminate between true ligands vs known nonbinders (therefore ...

      Abstract | HTMLFull Text HTML | PDFHi-Res PDF | PDFPDF w/ Links
  • Cover Image

    Statistical Potential for Modeling and Ranking of Protein–Ligand Interactions

    Hao Fan, Dina Schneidman-Duhovny, John J. Irwin, Guangqiang Dong, Brian K. Shoichet, and Andrej Sali
    Journal of Chemical Information and Modeling2011 51 (12), 3078-3092
    • Statistical Potential for Modeling and Ranking of Protein–Ligand Interactions

      Hao Fan, Dina Schneidman-Duhovny, John J. Irwin, Guangqiang Dong, Brian K. Shoichet, and Andrej Sali
      Journal of Chemical Information and Modeling2011 51 (12), 3078-3092

      Applications in structural biology and medicinal chemistry require protein–ligand scoring functions for two distinct tasks: (i) ranking different poses of a small molecule in a protein binding site and (ii) ranking different small molecules by their ...

      Abstract | HTMLFull Text HTML | PDFHi-Res PDF | PDFPDF w/ Links
  • Cover Image

    Improving VEGFR-2 Docking-Based Screening by Pharmacophore Postfiltering and Similarity Search Postprocessing

    Jesús M. Planesas, Rosa M. Claramunt, Jordi Teixidó, José I. Borrell, and Violeta I. Pérez-Nueno
    Journal of Chemical Information and Modeling2011 51 (4), 777-787
    • Improving VEGFR-2 Docking-Based Screening by Pharmacophore Postfiltering and Similarity Search Postprocessing

      Jesús M. Planesas, Rosa M. Claramunt, Jordi Teixidó, José I. Borrell, and Violeta I. Pérez-Nueno
      Journal of Chemical Information and Modeling2011 51 (4), 777-787

      Conventional docking-based virtual screening (VS) of chemical databases is based on the ranking of compounds according to the values retrieved by a scoring function (typically, the binding affinity estimation). However, using the most suitable scoring ...

      Abstract | HTMLFull Text HTML | PDFHi-Res PDF | PDFPDF w/ Links
  • Cover Image

    Rapid Context-Dependent Ligand Desolvation in Molecular Docking

    Michael M. Mysinger and Brian K. Shoichet
    Journal of Chemical Information and Modeling2010 50 (9), 1561-1573
    • Rapid Context-Dependent Ligand Desolvation in Molecular Docking

      Michael M. Mysinger and Brian K. Shoichet
      Journal of Chemical Information and Modeling2010 50 (9), 1561-1573

      In structure-based screens for new ligands, a molecular docking algorithm must rapidly score many molecules in multiple configurations, accounting for both the ligand’s interactions with receptor and its competing interactions with solvent. Here we ...

      Abstract | HTMLFull Text HTML | PDFHi-Res PDF | PDFPDF w/ Links
  • Cover Image

    Binding Energy Distribution Analysis Method (BEDAM) for Estimation of Protein−Ligand Binding Affinities

    Emilio Gallicchio, Mauro Lapelosa, and Ronald M. Levy
    Journal of Chemical Theory and Computation2010 6 (9), 2961-2977
    • Binding Energy Distribution Analysis Method (BEDAM) for Estimation of Protein−Ligand Binding Affinities

      Emilio Gallicchio, Mauro Lapelosa, and Ronald M. Levy
      Journal of Chemical Theory and Computation2010 6 (9), 2961-2977

      The binding energy distribution analysis method (BEDAM) for the computation of receptor−ligand standard binding free energies with implicit solvation is presented. The method is based on a well-established statistical mechanics theory of molecular ...

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Accession Codes

  • PDB: 3DFR
  • PDB: 1A4W
  • PDB: 2BBQ
  • PDB: 1B8O
  • PDB: 1E66
  • PDB: 181L
  • PDB: 1LGU
  • PDB: 1KE4
  • PDB: 1XEP

History

  • Published In Issue June 02, 2005
  • Received November 3, 2004

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Related Content

  • Evaluation of Docking Performance:  Comparative Data on Docking AlgorithmsJournal of Medicinal Chemistry
    • Evaluation of Docking Performance:  Comparative Data on Docking Algorithms

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      Journal of Medicinal Chemistry 2004 47 (3), pp 558–565

      Abstract: Docking molecules into their respective 3D macromolecular targets is a widely used method for lead optimization. However, the best known docking algorithms often fail to position the ligand in an orientation close to the experimental binding mode. It was ...

      Abstract | Full Text HTML | PDF w/ Links | Hi-Res PDF
  • Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-LactamaseJournal of Medicinal Chemistry
    • Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase

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      Journal of Medicinal Chemistry 2008 51 (8), pp 2502–2511

      Abstract: High-throughput screening (HTS) is widely used in drug discovery. Especially for screens of unbiased libraries, false positives can dominate “hit lists”; their origins are much debated. Here we determine the mechanism of every active hit from a screen of ...

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  • Benchmarking Sets for Molecular DockingJournal of Medicinal Chemistry
    • Benchmarking Sets for Molecular Docking

      Niu Huang, Brian K. Shoichet, and John J. Irwin
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      Abstract: Ligand enrichment among top-ranking hits is a key metric of molecular docking. To avoid bias, decoys should resemble ligands physically, so that enrichment is not simply a separation of gross features, yet be chemically distinct from them, so that they ...

      Abstract | Full Text HTML | PDF w/ Links | Hi-Res PDF

Other ACS content by these authors:

  • Alan P. Graves
  • Ruth Brenk
  • Brian K. Shoichet
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