Evidence map›Paper›PMID 26124721›Full record

ReviewFrontiers in pharmacology2015

Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes.

Hannu Raunio, Mira Kuusisto, Risto O Juvonen, Olli T Pentikäinen

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Pharmaceutics · 2022
    Article
  11. Review
  12. Toxicology reports · 2022
    Article
  13. Prevalence of five pharmacologically most importantArhiv za higijenu rada i toksikologiju · 2021
    Article
  14. Review
  15. Article
  16. Review
  17. Validation of in vitro methods for human cytochrome P450 enzyme induction: Outcome of a multi-laboratory study.Toxicology in vitro : an international journal published in association with BIBRA · 2019
    Article
  18. Article
  19. Article
  20. 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

4 authors.

Hannu RaunioSchool of Pharmacy, Faculty of Health Sciences, University of Eastern Finland Kuopio, Finland.
Mira KuusistoSchool of Pharmacy, Faculty of Health Sciences, University of Eastern Finland Kuopio, Finland ; Computational Bioscience Laboratory, Department of Biological and Environmental Science, Nanoscience Center, University of Jyväskylä Jyväskylä, Finland.
Risto O JuvonenSchool of Pharmacy, Faculty of Health Sciences, University of Eastern Finland Kuopio, Finland.
Olli T PentikäinenComputational Bioscience Laboratory, Department of Biological and Environmental Science, Nanoscience Center, University of Jyväskylä Jyväskylä, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adverse effects to humans and environment of only few chemicals are well known. Absorption, distribution, metabolism, and excretion (ADME) are the steps of pharmaco/toxicokinetics that determine the internal dose of chemicals to which the organism is exposed. Of all the xenobiotic-metabolizing enzymes, the cytochrome P450 (CYP) enzymes are the most important due to their abundance and versatility. Reactions catalyzed by CYPs usually turn xenobiotics to harmless and excretable metabolites, but sometimes an innocuous xenobiotic is transformed into a toxic metabolite. Data on ADME and toxicity properties of compounds are increasingly generated using in vitro and modeling (in silico) tools. Both physics-based and empirical modeling approaches are used. Numerous ligand-based and target-based as well as combined modeling methods have been employed to evaluate determinants of CYP ligand binding as well as predicting sites of metabolism and inhibition characteristics of test molecules. In silico prediction of CYP-ligand interactions have made crucial contributions in understanding (1) determinants of CYP ligand binding recognition and affinity; (2) prediction of likely metabolites from substrates; (3) prediction of inhibitors and their inhibition potency. Truly predictive models of toxic outcomes cannot be created without incorporating metabolic characteristics; in silico methods help producing such information and filling gaps in experimentally derived data. Currently modeling methods are not mature enough to replace standard in vitro and in vivo approaches, but they are already used as an important component in risk assessment of drugs and other chemicals.

Indexed as

cytochrome P450in silicometabolismmodelingxenobiotic

Identifiers

PMID26124721
PMCPMC4464169

What OpenQuestion holds

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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.