Evidence map›Paper›PMID 38766018›Full record

ArticlebioRxiv : the preprint server for biology2024

Ligandability at the membrane interface of GPx4 revealed through a reverse micelle fragment screening platform.

Courtney L Labrecque, Brian Fuglestad

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

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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

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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

5 · Who and what money

Authors and funding

2 authors.

Courtney L LabrecqueDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 22384, United States.ORCID 0000-0002-6075-853X
Brian FuglestadDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 22384, United States.ORCID 0000-0001-8304-8269

Funding

Peripheral membrane proteins and disease: tool development, basic investigations, and inhibitor designR35GM147221 · NIGMS · WISTAR INSTITUTE · PI Brian Fuglestad · 2022 to 2026
$2.1M
NIGMS NIH HHS R35 GM147221
6 · The paper itself

Abstract

While they account for a large portion of drug targets, membrane proteins (MPs) present a unique challenge for drug discovery. Peripheral membrane proteins (PMPs), a class of proteins that bind reversibly to membranes, are also difficult targets, particularly those that function only while bound to membranes. The protein-membrane interface in PMPs is often where functional interactions and catalysis occur, making it a logical target for inhibition. However, interfaces are underexplored spaces in inhibitor design and there is a need for enhanced methods for small-molecule ligand discovery. In an effort to better initiate drug discovery efforts for PMPs, this study presents a screening methodology using membrane-mimicking reverse micelles (mmRM) and NMR-based fragment screening to assess ligandability in the protein-membrane interface. The proof-of-principle target, glutathione peroxidase 4 (GPx4), is a lipid hydroperoxidase which is essential for the oxidative protection of membranes and thereby the prevention of ferroptosis. GPx4 inhibition is promising for therapy-resistant cancer therapy, but current inhibitors are generally covalent ligands with limited clinical utility. Presented here is the discovery of non-covalent small-molecule ligands for membrane-bound GPx4 revealed through the mmRM fragment screening methodology. The fragments were tested against GPx4 in bulk aqueous conditions and displayed little to no binding to the protein without embedment into the membrane. The 9 hits had varying affinities and partitioning coefficients and revealed properties of fragments that bind within the protein-membrane interface. Additionally, a secondary screen confirmed the potential to progress the fragments by enhancing the affinity from > 200 μM to ~15 μM with the addition of certain hydrophobic groups. This study presents an advancement of screening capabilities for membrane associated proteins, reveals ligandability within the GPx4 protein-membrane interface, and may serve as a starting point for developing non-covalent inhibitors of GPx4.

Indexed as

fragment-based drug discoveryGlutathione peroxidase 4peripheral membrane proteinprotein-ligand interactionsprotein-membrane interfaceProtein NMR

Identifiers

PMID38766018
PMCPMC11100811

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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.