Evidence map›Paper›PMID 23088273›Full record

ArticleFuture medicinal chemistry2012

Computational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and software.

Megan L Peach, Alexey V Zakharov, Ruifeng Liu, Angelo Pugliese, Gregory Tawa, Anders Wallqvist, Marc C Nicklaus

Abstract read
In one paragraph

Article in Future medicinal chemistry, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Computational toxicology (Amsterdam, Netherlands) · 2021
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Frontiers in pharmacology · 2019
    Review
  11. Article
  12. Article
  13. 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

7 authors.

Megan L PeachBasic Science Program, SAIC-Frederick, Inc.: CADD Group, Chemical Biology Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
Alexey V Zakharov
Ruifeng Liu
Angelo Pugliese
Gregory Tawa
Anders Wallqvist
Marc C Nicklaus

Funding

Tools for Prediction of Drug Metabolism and MetabolitesZIABC011336 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NICKLAUS, MARC · 2010 to 2020
$1.2M
CCR NIH HHS HHSN261200800001CIntramural NIH HHS ZIA BC011336NCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

Indexed as

Databases, FactualSoftwareComputational BiologyEnzymesHalf-LifePharmaceutical PreparationsEnzymesPharmaceutical Preparations

Identifiers

PMID23088273
PMCPMC3992830

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.