Evidence map›Paper›PMID 42420206›Full record

ArticleChemMedChem2026

Molecular Hybridization of Clinically Relevant P2X7 Antagonists.

Nicholas B Lynch, Charleigh T A Agius, André D J McKenzie, Jessica O'Driscoll, Angus Tolmie, Taylor R Garrett, Eryn Werry, Michael Kassiou

Abstract read
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In one paragraph

Article in ChemMedChem, 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

8 authors.

Nicholas B LynchSchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
Charleigh T A AgiusCentral Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
André D J McKenzieSchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
Jessica O'DriscollSchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
Angus TolmieSchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
Taylor R GarrettSchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
Eryn WerrySchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-6224-1286
Michael KassiouSchool of Chemistry, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-6655-0529

Funding

Australian Government Research Training Program.
6 · The paper itself

Abstract

The P2X7 receptor plays a pivotal role in the development of neurodegenerative disease states, yet no therapies targeting this receptor have reached the market to date. This work utilized a hybridization approach to combine clinically relevant antagonists AZD-9056 and JNJ-54175446 to discover new P2X7 antagonists. Here, we report the synthesis and in vitro and in silico evaluation of a library of 22 compounds to explore new chemical space around these clinically validated molecules. This study emphasizes the value of molecular hybridization in drug discovery and provides the basis for future P2X7 receptor antagonist development.

Indexed as

Purinergic P2X Receptor AntagonistsReceptors, Purinergic P2X7HumansMolecular StructureStructure-Activity RelationshipPurinergic P2X Receptor AntagonistsReceptors, Purinergic P2X7central nervous systemneurodegenerative diseaseP2X7P2X7R antagonistP2X receptor

Identifiers

PMID42420206
PMCPMC13346338

What OpenQuestion holds

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LicenceCC BY
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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.