Evidence map›Paper›PMID 37388277›Full record

ArticleComputational toxicology (Amsterdam, Netherlands)2023

Evaluating the utility of a high throughput thiol-containing fluorescent probe to screen for reactivity: A case study with the Tox21 library.

Grace Patlewicz, Katie Paul-Friedman, Keith Houck, Li Zhang, Ruili Huang, Menghang Xia, Jason Brown, Steven O Simmons

Abstract read
In one paragraph

Article in Computational toxicology (Amsterdam, Netherlands), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Grace PatlewiczCenter for Computational Toxicology & Exposure (CCTE), U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, 27709, USA.
Katie Paul-FriedmanCenter for Computational Toxicology & Exposure (CCTE), U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, 27709, USA.
Keith HouckCenter for Computational Toxicology & Exposure (CCTE), U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, 27709, USA.
Li ZhangNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Bethesda, MD 20892, USA.
Ruili HuangNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Bethesda, MD 20892, USA.
Menghang XiaNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Bethesda, MD 20892, USA.
Jason BrownCenter for Computational Toxicology & Exposure (CCTE), U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, 27709, USA.
Steven O SimmonsCenter for Computational Toxicology & Exposure (CCTE), U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, 27709, USA.

Funding

Toxicology in the 21st Century Program (Tox21) - Systems ToxicologyZIATR000038 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI XIA, MENGHANG · 2015 to 2025
$5.7M
Toxicology in the 21st Century Program (Tox21) - Computational ToxicologyZIATR000040 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI HUANG, RUILI · 2016 to 2025
$3.5M
Intramural EPA EPA999999
6 · The paper itself

Abstract

High-throughput screening (HTS) assays for bioactivity in the Tox21 program aim to evaluate an array of different biological targets and pathways, but a significant barrier to interpretation of these data is the lack of high-throughput screening (HTS) assays intended to identify non-specific reactive chemicals. This is an important aspect for prioritising chemicals to test in specific assays, identifying promiscuous chemicals based on their reactivity, as well as addressing hazards such as skin sensitisation which are not necessarily initiated by a receptor-mediated effect but act through a non-specific mechanism. Herein, a fluorescence-based HTS assay that allows the identification of thiol-reactive compounds was used to screen 7,872 unique chemicals in the Tox21 10K chemical library. Active chemicals were compared with profiling outcomes using structural alerts encoding electrophilic information. Random Forest classification models based on chemical fingerprints were developed to predict assay outcomes and evaluated through 10-fold stratified cross validation (CV). The mean CV Balanced Accuracy of the validation set was 0.648. The model developed shows promise as a tool to screen untested chemicals for their potential electrophilic reactivity based solely on chemical structural features.

Indexed as

in silico prediction modelsreaction mechanistic domainsreactivity assayTox21

Identifiers

PMID37388277
PMCPMC10304587

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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.