Evidence map›Paper›PMID 27994650›Full record

ArticleJournal of cheminformatics2016

Prediction of reacting atoms for the major biotransformation reactions of organic xenobiotics.

Anastasia V Rudik, Alexander V Dmitriev, Alexey A Lagunin, Dmitry A Filimonov, Vladimir V Poroikov

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
6.0field-weighted citation impact, top 4% 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, 30 citations in OpenAlex.

  1. Automated Annotation of Sites of Metabolism from Biotransformation Data.Journal of chemical information and modeling · 2025
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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

5 authors at 2 institutions in 1 country.

Anastasia V RudikLaboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry, 10/8 Pogodinskaya Str., Moscow, Russia 119121.ORCID 0000-0002-8916-9675
Alexander V DmitrievLaboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry, 10/8 Pogodinskaya Str., Moscow, Russia 119121.
Alexey A LaguninLaboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry, 10/8 Pogodinskaya Str., Moscow, Russia 119121 ; Medico-Biological Faculty, Pirogov Russian National Research Medical University, 1 Ostrovityanova Str., Moscow, Russia 117997.
Dmitry A FilimonovLaboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry, 10/8 Pogodinskaya Str., Moscow, Russia 119121.
Vladimir V PoroikovLaboratory for Structure-Function Based Drug Design, Institute of Biomedical Chemistry, 10/8 Pogodinskaya Str., Moscow, Russia 119121.
Institute of Biomedical Chemistry · RUPirogov Russian National Research Medical University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe knowledge of drug metabolite structures is essential at the early stage of drug discovery to understand the potential liabilities and risks connected with biotransformation. The determination of the site of a molecule at which a particular metabolic reaction occurs could be used as a starting point for metabolite identification. The prediction of the site of metabolism does not always correspond to the particular atom that is modified by the enzyme but rather is often associated with a group of atoms. To overcome this problem, we propose to operate with the term "reacting atom", corresponding to a single atom in the substrate that is modified during the biotransformation reaction. The prediction of the reacting atom(s) in a molecule for the major classes of biotransformation reactions is necessary to generate drug metabolites.

resultsSubstrates of the major human cytochromes P450 and UDP-glucuronosyltransferases from the Biovia Metabolite database were divided into nine groups according to their reaction classes, which are aliphatic and aromatic hydroxylation, N- and O-glucuronidation, N-, S- and C-oxidation, and N- and O-dealkylation. Each training set consists of positive and negative examples of structures with one labelled atom. In the positive examples, the labelled atom is the reacting atom of a particular reaction that changed adjacency. Negative examples represent non-reacting atoms of a particular reaction. We used Labelled Multilevel Neighbourhoods of Atoms descriptors for the designation of reacting atoms. A Bayesian-like algorithm was applied to estimate the structure-activity relationships. The average invariant accuracy of prediction obtained in leave-one-out and 20-fold cross-validation procedures for five human isoforms of cytochrome P450 and all isoforms of UDP-glucuronosyltransferase varies from 0.86 to 0.99 (0.96 on average).

conclusionsWe report that reacting atoms may be predicted with reasonable accuracy for the major classes of metabolic reactions-aliphatic and aromatic hydroxylation, N- and O-glucuronidation, N-, S- and C-oxidation, and N- and O-dealkylation. The proposed method is implemented as a freely available web service at http://www.way2drug.com/RA and may be used for the prediction of the most probable biotransformation reaction(s) and the appropriate reacting atoms in drug-like compounds.Graphical abstract.

Indexed as

Aliphatic hydroxylationAromatic hydroxylationBiotransformationC-oxidationDrug metabolismLMNA descriptorsN-dealkylationN-glucuronidationN-oxidationO-dealkylationO-glucuronidationP450PASSPredictionReacting atomsSite of metabolismSOMSOMPS-oxidationXenobiotic

Identifiers

PMID27994650
PMCPMC5127045
OpenAlexW2558556025

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.