Evidence map›Paper›PMID 26403354›Full record

ArticleBMC bioinformatics2015

2D and 3D similarity landscape analysis identifies PARP as a novel off-target for the drug Vatalanib.

Bjoern-Oliver Gohlke, Tim Overkamp, Anja Richter, Antje Richter, Peter T Daniel, Bernd Gillissen, Robert Preissner

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 17 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

7 authors at 3 institutions in 1 country.

Bjoern-Oliver GohlkeStructural Bioinformatics Group, Charite - University Medicine Berlin & ECRC, Lindenberger Weg 80, 13125, Berlin, Germany. bjoern-oliver.gohlke@charite.de.
Tim OverkampDepartment of Hematology, Oncology and Tumor Immunology, University Medical Center Charité, Campus Berlin-Buch, Humboldt University Berlin, Berlin, Germany. tim@overkamp.de.
Anja RichterGerman Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany. anja.richter@charite.de.
Antje RichterDepartment of Hematology, Oncology and Tumor Immunology, University Medical Center Charité, Campus Berlin-Buch, Humboldt University Berlin, Berlin, Germany. antje.richter@charite.de.
Peter T DanielDepartment of Hematology, Oncology and Tumor Immunology, University Medical Center Charité, Campus Berlin-Buch, Humboldt University Berlin, Berlin, Germany. peter.daniel@charite.de.
Bernd GillissenDepartment of Hematology, Oncology and Tumor Immunology, University Medical Center Charité, Campus Berlin-Buch, Humboldt University Berlin, Berlin, Germany. bernhard.gillissen@charite.de.
Robert PreissnerStructural Bioinformatics Group, Charite - University Medicine Berlin & ECRC, Lindenberger Weg 80, 13125, Berlin, Germany. robert.preissner@charite.de.
German Cancer Research Center · DECharité - Universitätsmedizin Berlin · DEHumboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSearching for two-dimensional (2D) structural similarities is a useful tool to identify new active compounds in drug-discovery programs. However, as 2D similarity measures neglect important structural and functional features, similarity by 2D might be underestimated. In the present study, we used combined 2D and three-dimensional (3D) similarity comparisons to reveal possible new functions and/or side-effects of known bioactive compounds.

resultsWe utilised more than 10,000 compounds from the SuperTarget database with known inhibition values for twelve different anti-cancer targets. We performed all-against-all comparisons resulting in 2D similarity landscapes. Among the regions with low 2D similarity scores are inhibitors of vascular endothelial growth factor receptor (VEGFR) and inhibitors of poly ADP-ribose polymerase (PARP). To demonstrate that 3D landscape comparison can identify similarities, which are untraceable in 2D similarity comparisons, we analysed this region in more detail. This 3D analysis showed the unexpected structural similarity between inhibitors of VEGFR and inhibitors of PARP. Among the VEGFR inhibitors that show similarities to PARP inhibitors was Vatalanib, an oral "multi-targeted" small molecule protein kinase inhibitor being studied in phase-III clinical trials in cancer therapy. An in silico docking simulation and an in vitro HT universal colorimetric PARP assay confirmed that the VEGFR inhibitor Vatalanib exhibits off-target activity as a PARP inhibitor, broadening its mode of action.

conclusionIn contrast to the 2D-similarity search, the 3D-similarity landscape comparison identifies new functions and side effects of the known VEGFR inhibitor Vatalanib.

Indexed as

Binding SitesColorimetryComputational BiologyDrug DiscoveryHumansMCF-7 CellsMicroscopy, FluorescenceMolecular Docking SimulationPhthalazinesPoly(ADP-ribose) Polymerase InhibitorsPoly(ADP-ribose) PolymerasesProtein BindingProtein Structure, TertiaryPyridinesVascular Endothelial Growth Factor APhthalazinesPoly(ADP-ribose) Polymerase InhibitorsPoly(ADP-ribose) PolymerasesPyridinesVascular Endothelial Growth Factor Avatalanib

Identifiers

PMID26403354
PMCPMC4582733
OpenAlexW1917819059

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.