Evidence map›Paper›PMID 24098414›Full record

ArticlePloS one2013

Ligand pose and orientational sampling in molecular docking.

Ryan G Coleman, Michael Carchia, Teague Sterling, John J Irwin, Brian K Shoichet

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers.

0numbers the graph read from it
0cells of the map it votes in
125citing 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

125 citing papers in PubMed.

  1. γ-glutamyl carboxylase inhibition by Anisindione.Structure (London, England : 1993) · 2026
    Article
  2. Article
  3. Review
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  5. Article
  6. Article
  7. Article
  8. DOCKweb: a web-based GUI platform for molecular modeling with DOCK6.Journal of computer-aided molecular design · 2026
    Article
  9. Article
  10. Article
  11. Quantum computing applications in drug discovery.Briefings in bioinformatics · 2026
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

65 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

5 authors.

Ryan G ColemanDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America.
Michael Carchia
Teague Sterling
John J Irwin
Brian K Shoichet

Funding

A Web-Based Automatic Virtual Screening SystemR01GM071896 · NIGMS · UNIVERSITY OF TORONTO · PI IRWIN, JOHN J. · 2004 to 2024
$6.0M
DESIGN AND EXPERIMENTAL TESTING OF NEW DOCKING METHODSR01GM059957 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SHOICHET, BRIAN K · 1999 to 2017
$4.4M
Sampling Resolution In Molecular Docking Applied to Beta2-adrenergic ReceptorF32GM096544 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COLEMAN, RYAN GEOFFREY · 2011 to 2012
$101k
NIGMS NIH HHS F32 GM096544NIGMS NIH HHS F32GM096544NIGMS NIH HHS R01 GM059957NIGMS NIH HHS R01 GM071896NIGMS NIH HHS R01 GM59957NIGMS NIH HHS R01 GM71896
6 · The paper itself

Abstract

Molecular docking remains an important tool for structure-based screening to find new ligands and chemical probes. As docking ambitions grow to include new scoring function terms, and to address ever more targets, the reliability and extendability of the orientation sampling, and the throughput of the method, become pressing. Here we explore sampling techniques that eliminate stochastic behavior in DOCK3.6, allowing us to optimize the method for regularly variable sampling of orientations. This also enabled a focused effort to optimize the code for efficiency, with a three-fold increase in the speed of the program. This, in turn, facilitated extensive testing of the method on the 102 targets, 22,805 ligands and 1,411,214 decoys of the Directory of Useful Decoys-Enhanced (DUD-E) benchmarking set, at multiple levels of sampling. Encouragingly, we observe that as sampling increases from 50 to 500 to 2000 to 5000 to 20,000 molecular orientations in the binding site (and so from about 1×10(10) to 4×10(10) to 1×10(11) to 2×10(11) to 5×10(11) mean atoms scored per target, since multiple conformations are sampled per orientation), the enrichment of ligands over decoys monotonically increases for most DUD-E targets. Meanwhile, including internal electrostatics in the evaluation ligand conformational energies, and restricting aromatic hydroxyls to low energy rotamers, further improved enrichment values. Several of the strategies used here to improve the efficiency of the code are broadly applicable in the field.

Indexed as

AlgorithmsComputer GraphicsLigandsMolecular ConformationMolecular Docking SimulationPhenolsThermodynamicsLigandsPhenols

Identifiers

PMID24098414
PMCPMC3787967

What OpenQuestion holds

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LicenceCC BY
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.