Evidence map›Paper›PMID 30070179›Full record

ArticleDrug metabolism letters2018

Using LC Retention Times in Organic Structure Determination: Drug Metabolite Identification.

William L Fitch, Cyrus Khojasteh, Ignacio Aliagas, Kevin Johnson

Abstract read
In one paragraph

Article in Drug metabolism letters, 2018. 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. Review
  2. Review
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.

William L FitchDepartment of Gastroenterology and Hepatology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, United States.
Cyrus KhojastehDepartment of Drug Metabolism and Pharmacokinetics 1 DNA Way MS 412a, Genentech Inc., South San Francisco, CA 94080, United States.
Ignacio AliagasDiscovery Chemistry, 1 DNA Way, Genentech Inc., South San Francisco, CA 94080, United States.
Kevin JohnsonDepartment of Drug Metabolism and Pharmacokinetics 1 DNA Way MS 412a, Genentech Inc., South San Francisco, CA 94080, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a continued need for improvements in the efficiency of metabolite structure elucidation.

objectiveWe propose to take LC Retention Time (RT) into consideration during the process of structure determination.

methodsHerein, we develop a simple methodology that employs a Chromatographic Hydrophobicity Index (CHI) framework for standardizing LC conditions and introduce and utilize the concept of a predictable CHI change upon Phase 1 biotransformation (CHIbt). Through the analysis of literature examples, we offer a Quantitative Structure-Retention Relationship (QSRR) for several types of biotransformation (especially hydroxylation) using physicochemical properties (clogP, hydrogen bonding).

resultsThe CHI system for retention indexing is shown to be practical and simple to implement. A database of CHIbt values has been created from re-incubation of 3 compounds and from analysis of an additional 17 datasets from the literature. Application of this database is illustrated.

conclusionIn our experience, this simple methodology allows complementing the discovery efforts that saves resources for in-depth characterization using NMR.

Indexed as

AtorvastatinBiotransformationCarbanilidesChromatography, LiquidDemethylationHumansHydrogen BondingHydrophobic and Hydrophilic InteractionsHydroxylationMass SpectrometryMicrosomes, LiverMolecular StructureOxidation-ReductionQuantitative Structure-Activity RelationshipTime FactorsWorkflowAtorvastatinCarbanilidestriclocarbanCHI systemDrug metabolite identificationliquid chromatographymass spectrometry (MS).RTRT prediction

Identifiers

PMID30070179
PMCPMC6350196

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LicenceCC BY-NC
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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.