Cross-Species Molecular Docking Method to Support Predictions of Species Susceptibility to Chemical Effects.

Peter G Schumann, Daniel Chang, Sally Mayasich, Sara Vliet, Terry Brown, Carlie A LaLone

Abstract read

In one paragraph

Article in Computational toxicology (Amsterdam, Netherlands), 2024. 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.

A NAMs-based framework for screening the endocrine-disrupting potential of plastic additives using cross-species molecular docking andFrontiers in toxicology · 2026
Article
Advancements in toxicological risk assessment: integrating Ferguson's principle, computational models, and drug safety guidelines, a comprehensive framework for improving risk assessment and resource management in toxicology.Toxicology research · 2025
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

6 authors.

Peter G SchumannOak Ridge Institute for Science and Education, Duluth, Minnesota, USA.

Daniel ChangU.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Chemical Characterization and Exposure Division, Research Triangle Park, North Carolina, USA.

Sally MayasichAquatic Sciences Center, University of Wisconsin-Madison, Madison, Wisconsin, USA.

Sara VlietU.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.

Terry BrownU.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Scientific Computing and Data Curation Division, Duluth, Minnesota, USA.

Carlie A LaLoneU.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Great Lakes Toxicology and Ecology Division, Duluth, Minnesota, USA.

Funding

Intramural EPA EPA999999

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Androgen receptorCross-speciesMolecular dockingNew Approach MethodologiesPredictive toxicologySequence Alignment to Predict Across Species Susceptibility (SeqAPASS)

Identifiers

PMID39381055

DOI10.1016/j.comtox.2024.100319

PMCPMC11457042

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.