Evidence map›Paper›PMID 27803745›Full record

ArticleJournal of cheminformatics2016

Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance.

Ludovic Chaput, Juan Martinez-Sanz, Nicolas Saettel, Liliane Mouawad

Open access · goldAbstract read
In one paragraph

Article in Journal of cheminformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
8.7field-weighted citation impact, top 2% of its field
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

48 citing papers in PubMed, 119 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Ludovic ChaputInstitut Curie - PSL Research University, Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Centre Universitaire, Orsay, Bâtiment 112, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay Cedex, France ; Inserm, U1196, Orsay Cedex, France ; CNRS, UMR 9187, Orsay Cedex, France.
Juan Martinez-SanzInstitut Curie - PSL Research University, Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Centre Universitaire, Orsay, Bâtiment 112, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay Cedex, France ; Inserm, U1196, Orsay Cedex, France ; CNRS, UMR 9187, Orsay Cedex, France.
Nicolas SaettelInstitut Curie - PSL Research University, Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Centre Universitaire, Orsay, Bâtiment 112, 91405 Orsay Cedex, France ; Inserm, U1196, Orsay Cedex, France ; CNRS, UMR 9187, Orsay Cedex, France ; School of Pharmacy, University of Caen, Normandy, Boulevard Becquerel, 14032 Caen, France.
Liliane MouawadInstitut Curie - PSL Research University, Chemistry, Modelling and Imaging for Biology (CMIB), Centre de Recherche, Centre Universitaire, Orsay, Bâtiment 112, 91405 Orsay Cedex, France ; Paris-Sud University, Orsay Cedex, France ; Inserm, U1196, Orsay Cedex, France ; CNRS, UMR 9187, Orsay Cedex, France.
Institut Curie · FRUniversité Paris Sciences et Lettres · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn a structure-based virtual screening, the choice of the docking program is essential for the success of a hit identification. Benchmarks are meant to help in guiding this choice, especially when undertaken on a large variety of protein targets. Here, the performance of four popular virtual screening programs, Gold, Glide, Surflex and FlexX, is compared using the Directory of Useful Decoys-Enhanced database (DUD-E), which includes 102 targets with an average of 224 ligands per target and 50 decoys per ligand, generated to avoid biases in the benchmarking. Then, a relationship between these program performances and the properties of the targets or the small molecules was investigated.

resultsThe comparison was based on two metrics, with three different parameters each. The BEDROC scores with α = 80.5, indicated that, on the overall database, Glide succeeded (score > 0.5) for 30 targets, Gold for 27, FlexX for 14 and Surflex for 11. The performance did not depend on the hydrophobicity nor the openness of the protein cavities, neither on the families to which the proteins belong. However, despite the care in the construction of the DUD-E database, the small differences that remain between the actives and the decoys likely explain the successes of Gold, Surflex and FlexX. Moreover, the similarity between the actives of a target and its crystal structure ligand seems to be at the basis of the good performance of Glide. When all targets with significant biases are removed from the benchmarking, a subset of 47 targets remains, for which Glide succeeded for only 5 targets, Gold for 4 and FlexX and Surflex for 2.

conclusionThe performance dramatic drop of all four programs when the biases are removed shows that we should beware of virtual screening benchmarks, because good performances may be due to wrong reasons. Therefore, benchmarking would hardly provide guidelines for virtual screening experiments, despite the tendency that is maintained, i.e., Glide and Gold display better performance than FlexX and Surflex. We recommend to always use several programs and combine their results. Graphical AbstractSummary of the results obtained by virtual screening with the four programs, Glide, Gold, Surflex and FlexX, on the 102 targets of the DUD-E database. The percentage of targets with successful results, i.e., with BDEROC(α = 80.5) > 0.5, when the entire database is considered are in Blue, and when targets with biased chemical libraries are removed are in Red.

Indexed as

BEDROCBenchmarkDockingDUD-EFlexXGlideGoldStructure-based virtual screeningSurflex

Identifiers

PMID27803745
PMCPMC5066283
OpenAlexW2536259549

What OpenQuestion holds

Textmetadata
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.