Evidence map›Paper›PMID 22569590›Full record

ArticleJournal of computer-aided molecular design2012

Surflex-Dock: Docking benchmarks and real-world application.

Russell Spitzer, Ajay N Jain

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 102 papers.

0numbers the graph read from it
0cells of the map it votes in
102citing 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

102 citing papers in PubMed.

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  19. Article
  20. Computer-Assisted Design of Peptide-Based Radiotracers.International journal of molecular sciences · 2023
    Review

42 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

2 authors.

Russell SpitzerDeparment of Bioengineering and Therapeutic Sciences, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
Ajay N Jain

Funding

BMI Bioinformatics Training GrantsT32GM067547 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HERNANDEZ, RYAN D. · 2003 to 2022
$6.6M
Machine Learning in Chemistry and BiologyR01GM070481 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JAIN, AJAY N · 2005 to 2013
$2.5M
NIGMS NIH HHS GM070481NIGMS NIH HHS R01 GM070481NIGMS NIH HHS T32 GM067547
6 · The paper itself

Abstract

Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein-ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.

Indexed as

AlgorithmsLigandsProtein ConformationBinding SitesComputer SimulationCrystallography, X-RayModels, MolecularProtein BindingProteinsSoftwareStructural Homology, ProteinLigandsProteins

Identifiers

PMID22569590
PMCPMC3398190

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.