Evidence map›Paper›PMID 22569591›Full record

ArticleJournal of computer-aided molecular design2012

Docking and scoring with ICM: the benchmarking results and strategies for improvement.

Marco A C Neves, Maxim Totrov, Ruben Abagyan

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers.

0numbers the graph read from it
0cells of the map it votes in
168citing 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

168 citing papers in PubMed.

  1. Review
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  15. Activity of STAMP inhibitors inBlood neoplasia · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Deciphering the language of mingling lipids and proteins.Current opinion in structural biology · 2025
    Review
  20. Article

108 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

3 authors.

Marco A C NevesSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Maxim Totrov
Ruben Abagyan

Funding

Project 3U54GM094618 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI STEVENS, RAYMOND C · 2010 to 2014
$17.1M
Structure, Dynamics and Activation Mechanisms of Chemokine ReceptorsU01GM094612 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHANCE, MARK R · 2010 to 2014
$4.5M
Macromolecular DockingR01GM071872 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ABAGYAN, RUBEN · 2004 to 2017
$4.2M
NIGMS NIH HHS R01 GM071872NIGMS NIH HHS U01 GM094612NIGMS NIH HHS U54 GM094618
6 · The paper itself

Abstract

Flexible docking and scoring using the internal coordinate mechanics software (ICM) was benchmarked for ligand binding mode prediction against the 85 co-crystal structures in the modified Astex data set. The ICM virtual ligand screening was tested against the 40 DUD target benchmarks and 11-target WOMBAT sets. The self-docking accuracy was evaluated for the top 1 and top 3 scoring poses at each ligand binding site with near native conformations below 2 Å RMSD found in 91 and 95% of the predictions, respectively. The virtual ligand screening using single rigid pocket conformations provided the median area under the ROC curves equal to 69.4 with 22.0% true positives recovered at 2% false positive rate. Significant improvements up to ROC AUC = 82.2 and ROC((2%)) = 45.2 were achieved following our best practices for flexible pocket refinement and out-of-pocket binding rescore. The virtual screening can be further improved by considering multiple conformations of the target.

Indexed as

AlgorithmsComputer SimulationLigandsBinding SitesCrystallography, X-RayDrug DiscoveryHumansModels, MolecularProtein BindingProtein ConformationProteinsSoftwareLigandsProteins

Identifiers

PMID22569591
PMCPMC3398187

What OpenQuestion holds

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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.