Evidence map›Paper›PMID 42455829›Full record

ArticlePloS one2026

Binding Affinity Ranking at the Molecular Initiating Event (BARMIE): An open-source computational pipeline for the rapid screening of chemical interactions with steroid receptors from many species.

Fernando Calahorro, Parsa Fouladi, Alessandro Pandini, Matloob Khushi, Yogendra Gaihre, Nic R Bury

Abstract read
In one paragraph

Article in PloS one, 2026. 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

6 authors.

Fernando CalahorroUniversity of Southampton, School of Ocean and Earth Science, National Oceanography Centre, European Way, Southampton, United Kingdom.
Parsa FouladiBrunel University of London, College of Engineering, Design and Physical Sciences, Department of Computer Science, Wilfred Brown Building, Uxbridge, United Kingdom.
Alessandro PandiniBrunel University of London, College of Engineering, Design and Physical Sciences, Department of Computer Science, Wilfred Brown Building, Uxbridge, United Kingdom.ORCID https://orcid.org/0000-0002-4158-233X
Matloob KhushiBrunel University of London, College of Engineering, Design and Physical Sciences, Department of Computer Science, Wilfred Brown Building, Uxbridge, United Kingdom.
Yogendra GaihreUniversity of Southampton, School of Ocean and Earth Science, National Oceanography Centre, European Way, Southampton, United Kingdom.
Nic R BuryUniversity of Southampton, School of Ocean and Earth Science, National Oceanography Centre, European Way, Southampton, United Kingdom.ORCID https://orcid.org/0000-0001-6048-6338

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A challenge in ecological risk assessment is identifying the chemicals that pose the greatest threat and determining which species are most vulnerable to them. To help address this, this study has developed an in-silico open-source tool called BARMIE (Binding Affinity Ranking at the Molecular Initiating Event) to rapidly predict the chemical binding affinity of steroid receptor proteins to synthetic steroids to identify potentially vulnerable species and chemicals of concern. BARMIE was used to screen 163 teleost fish glucocorticoid receptors (GRs) for binding to the natural ligand cortisol and to 10 synthetic glucocorticoid drugs (GCs) designed to interact within the ligand-binding pocket (LBP) of GRs. BARMIE identified species from the superorder Protacanthopterygii with high-affinity GRs to synthetic GCs (e.g., vulnerable species).. BARMIE was also used to screen binding profiles of compounds in the Medicine for Malaria Venture Global Health Priority Box to rainbow trout GRs (rtGR1 and rtGR2). Of the 178 compounds, 24 and 36 bind within the LBP of rtGR1 and rtGR2, respectively. For 30 of these compounds, transactivation activity was assessed at 1µM in the presence or absence of 1µM cortisol and confirmed 2 compounds with agonistic properties (e.g., chemicals of concern) that would require further in vitro and/or in vivo studies to assess the environmental risk. BARMIE can rapidly generate predicted binding affinities for 100's of species and chemicals as a first screen in environmental risk assessment to provide information on which substances to prioritise in downstream tests.

Indexed as

Computational BiologyReceptors, GlucocorticoidReceptors, SteroidAnimalsBinding SitesComputer SimulationFishesGlucocorticoidsHydrocortisoneLigandsOncorhynchus mykissProtein BindingGlucocorticoidsHydrocortisoneLigandsReceptors, GlucocorticoidReceptors, Steroid

Identifiers

PMID42455829
PMCPMC13372184

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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.