Evidence map›Paper›PMID 25750602›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society

A 'rule of 0.5' for the metabolite-likeness of approved pharmaceutical drugs.

Steve O Hagan, Neil Swainston, Julia Handl, Douglas B Kell

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

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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.

Steve O HaganSchool of Chemistry, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK ; The Manchester Institute of Biotechnology, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK.
Neil SwainstonThe Manchester Institute of Biotechnology, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK ; School of Computer Science, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK.
Julia HandlManchester Business School, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK.
Douglas B KellSchool of Chemistry, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK ; The Manchester Institute of Biotechnology, The University of Manchester, 131 Princess St, Manchester, M1 7DN UK.

Funding

Biotechnology and Biological Sciences Research Council BB/K019783/1Biotechnology and Biological Sciences Research Council BB/M017702/1
6 · The paper itself

Abstract

We exploit the recent availability of a community reconstruction of the human metabolic network ('Recon2') to study how close in structural terms are marketed drugs to the nearest known metabolite(s) that Recon2 contains. While other encodings using different kinds of chemical fingerprints give greater differences, we find using the 166 Public MDL Molecular Access (MACCS) keys that 90 % of marketed drugs have a Tanimoto similarity of more than 0.5 to the (structurally) 'nearest' human metabolite. This suggests a 'rule of 0.5' mnemonic for assessing the metabolite-like properties that characterise successful, marketed drugs. Multiobjective clustering leads to a similar conclusion, while artificial (synthetic) structures are seen to be less human-metabolite-like. This 'rule of 0.5' may have considerable predictive value in chemical biology and drug discovery, and may represent a powerful filter for decision making processes.

Indexed as

CheminformaticsDrug-likenessGenome-wide metabolic reconstructionKNIMEMetabolite-likenessRecon 2

Identifiers

PMID25750602
PMCPMC4342520

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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.