Evidence map›Paper›PMID 38641346›Full record

ArticleDrug metabolism and disposition: the biological fate of chemicals2024

Differential Tissue Abundance of Membrane-Bound Drug Metabolizing Enzymes and Transporter Proteins by Global Proteomics.

Dilip Kumar Singh, Deepak Ahire, Dmitri R Davydov, Bhagwat Prasad

Open access · bronzeAbstract read
In one paragraph

Article in Drug metabolism and disposition: the biological fate of chemicals, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
8.4field-weighted citation impact, top 2% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

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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 at 1 institution in 1 country.

Dilip Kumar SinghDepartment of Pharmaceutical Sciences, Washington State University, Spokane, Washington (D.K.S., D.A., B.P.); and Department of Chemistry, Washington State University, Pullman, Washington (D.R.D.).ORCID 0000-0001-7248-6714
Deepak AhireDepartment of Pharmaceutical Sciences, Washington State University, Spokane, Washington (D.K.S., D.A., B.P.); and Department of Chemistry, Washington State University, Pullman, Washington (D.R.D.).ORCID 0000-0001-8537-6047
Dmitri R DavydovDepartment of Pharmaceutical Sciences, Washington State University, Spokane, Washington (D.K.S., D.A., B.P.); and Department of Chemistry, Washington State University, Pullman, Washington (D.R.D.).ORCID 0000-0001-8520-0033
Bhagwat PrasadDepartment of Pharmaceutical Sciences, Washington State University, Spokane, Washington (D.K.S., D.A., B.P.); and Department of Chemistry, Washington State University, Pullman, Washington (D.R.D.) bhagwat.prasad@wsu.edu.ORCID 0000-0002-9090-0912
Washington State University Spokane · US

Funding

Inter-Enzyme Crosstalk in the Cytochrome P450 Ensemble: Implications for the Effects of Alcohol on Drug Metabolism and Alcohol-Drug InteractionsR01AA030155 · NIAAA · WASHINGTON STATE UNIVERSITY · PI DAVYDOV, DMITRI R, PRASAD, BHAGWAT · 2022 to 2025
$2.0M
NIAAA NIH HHS R01 AA030155
6 · The paper itself

Abstract

Protein abundance data of drug-metabolizing enzymes and transporters (DMETs) are useful for scaling in vitro and animal data to humans for accurate prediction and interpretation of drug clearance and toxicity. Targeted DMET proteomics that relies on synthetic stable isotope-labeled surrogate peptides as calibrators is routinely used for the quantification of selected proteins; however, the technique is limited to the quantification of a small number of proteins. Although the global proteomics-based total protein approach (TPA) is emerging as a better alternative for large-scale protein quantification, the conventional TPA does not consider differential sequence coverage by identifying unique peptides across proteins. Here, we optimized the TPA approach by correcting protein abundance data by the sequence coverage, which was applied to quantify 54 DMETs for characterization of 1) differential tissue DMET abundance in the human liver, kidney, and intestine, and 2) interindividual variability of DMET proteins in individual intestinal samples (

Indexed as

LiverMembrane Transport ProteinsProteomicsCytochrome P-450 Enzyme SystemFemaleGlucuronosyltransferaseGlutathione TransferaseHumansInactivation, MetabolicIntestinal MucosaKidneyMaleMultidrug Resistance-Associated Protein 2Pharmaceutical PreparationsABCC2 protein, humanCytochrome P-450 Enzyme SystemGlucuronosyltransferaseGlutathione TransferaseMembrane Transport ProteinsMultidrug Resistance-Associated Protein 2Pharmaceutical Preparations

Identifiers

PMID38641346
PMCPMC11495667
OpenAlexW4394951975

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.