Evidence map›Paper›PMID 28884009›Full record

ArticleFuture science OA2017

Identifying relationships between unrelated pharmaceutical target proteins on the basis of shared active compounds.

Filip Miljković, Ryo Kunimoto, Jürgen Bajorath

Abstract read
In one paragraph

Article in Future science OA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Moving targets in drug discovery.Scientific reports · 2020
    Article
  2. Article
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.

Filip MiljkovićDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
Ryo KunimotoDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.
Jürgen BajorathDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstr. 2, D-53113 Bonn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimComputational exploration of small-molecule-based relationships between target proteins from different families. MATERIALS &

methodsTarget annotations of drugs and other bioactive compounds were systematically analyzed on the basis of high-confidence activity data.

resultsA total of 286 novel chemical links were established between distantly related or unrelated target proteins. These relationships involved a total of 1859 bioactive compounds including 147 drugs and 141 targets.

conclusionComputational analysis of large amounts of compounds and activity data has revealed unexpected relationships between diverse target proteins on the basis of compounds they share. These relationships are relevant for drug discovery efforts. Target pairs that we have identified and associated compound information are made freely available.

Indexed as

bioactive compoundscompound-based target relationshipsligand-binding characteristicstarget familiestarget proteins

Identifiers

PMID28884009
PMCPMC5583696

What OpenQuestion holds

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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.