Evidence map›Paper›PMID 33494610›Full record

ArticleJournal of chemical information and modeling2021

Property-Unmatched Decoys in Docking Benchmarks.

Reed M Stein, Ying Yang, Trent E Balius, Matt J O'Meara, Jiankun Lyu, Jennifer Young, Khanh Tang, Brian K Shoichet, John J Irwin

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing 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

77 citing papers in PubMed.

  1. Article
  2. Article
  3. Library Docking for Cannabinoid-2 Receptor Ligands.Journal of medicinal chemistry · 2026
    Article
  4. Review
  5. Article
  6. Discovery of Covalent Ligands with AlphaFold3.Journal of the American Chemical Society · 2026
    Article
  7. Review
  8. Fine-Tuning DiffDock-L for Allosteric Kinase Docking.Journal of chemical information and modeling · 2026
    Article
  9. Library docking for Cannabinoid-2 Receptor ligands.bioRxiv : the preprint server for biology · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. AnCurrent drug targets · 2026
    Article
  16. Discovery of Putative GyrB Inhibitors againstCurrent medicinal chemistry · 2026
    Article
  17. Article
  18. Article
  19. Article
  20. Article

17 more citing papers are in PubMed but not listed here.

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.

Reed M SteinDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.
Ying YangDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.
Trent E BaliusCancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., P.O. Box B, Frederick, Maryland 21702, United States.
Matt J O'MearaDepartment of Computational Medicine and Bioinformatics, University of Michigan, Palmer Commons, 100 Washtenaw Ave. #2017, Ann Arbor, Michigan 48109, United States.
Jiankun LyuDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.
Jennifer YoungDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.
Khanh TangDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.
Brian K ShoichetDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.ORCID 0000-0002-6098-7367
John J IrwinDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California 94158, United States.

Funding

Development and Testing of New Computational Methods for Ligand Discovery and MechanismR35GM122481 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Brian K Shoichet · 2017 to 2026
$8.5M
A Web-Based Automatic Virtual Screening SystemR01GM071896 · NIGMS · UNIVERSITY OF TORONTO · PI IRWIN, JOHN J. · 2004 to 2024
$6.0M
NIGMS NIH HHS R01 GM071896NIGMS NIH HHS R35 GM122481
6 · The paper itself

Abstract

Enrichment of ligands versus property-matched decoys is widely used to test and optimize docking library screens. However, the unconstrained optimization of enrichment alone can mislead, leading to false confidence in prospective performance. This can arise by over-optimizing for enrichment against property-matched decoys, without considering the full spectrum of molecules to be found in a true large library screen. Adding decoys representing charge extrema helps mitigate over-optimizing for electrostatic interactions. Adding decoys that represent the overall characteristics of the library to be docked allows one to sample molecules not represented by ligands and property-matched decoys but that one will encounter in a prospective screen. An optimized version of the DUD-E set (DUDE-Z), as well as Extrema and sets representing broad features of the library (Goldilocks), is developed here. We also explore the variability that one can encounter in enrichment calculations and how that can temper one's confidence in small enrichment differences. The new tools and new decoy sets are freely available at http://tldr.docking.org and http://dudez.docking.org.

Indexed as

LigandsModels, MolecularProspective StudiesProtein BindingLigands

Identifiers

PMID33494610
PMCPMC7913603

What OpenQuestion holds

Textmetadata
LicenceTDM
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.