Evidence map›Paper›PMID 41532565›Full record

ArticleFEBS letters2026

Cell wall target fragment discovery using a low-cost, minimal fragment library.

Kaizhou Yan, Mathew Stanley, Olawale Raimi, Andrew T Ferenbach, Helge C Dorfmueller, Daan M F van Aalten

Abstract read
In one paragraph

Article in FEBS letters, 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.

Kaizhou YanDivision of Molecular, Cell and Developmental Biology, School of Life Sciences, University of Dundee, UK.
Mathew StanleyDivision of Molecular, Cell and Developmental Biology, School of Life Sciences, University of Dundee, UK.
Olawale RaimiMedical Research Council Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, UK.
Andrew T FerenbachDepartment of Molecular Biology and Genetics, Aarhus University, Denmark.
Helge C DorfmuellerDivision of Molecular Microbiology, School of Life Sciences, University of Dundee, UK.
Daan M F van AaltenDivision of Molecular, Cell and Developmental Biology, School of Life Sciences, University of Dundee, UK.ORCID https://orcid.org/0000-0002-1499-6908

Funding

Medical Research Council V001094Novo Nordisk Fonden NNF21OC0065969Novo Nordisk Fonden NNF24SA0092593Villum Fonden 00054496Wellcome Trust 200208Wellcome Trust 225350/Z/22/Z
6 · The paper itself

Abstract

Fragment-based inhibitor design is an established and widely used approach in drug discovery pipelines. Despite several examples of drugs originating from this approach, the identification of fragments still suffers from issues with solubility, reactivity, cost and worldwide accessibility. Here, we design a low-cost minimal fragment library (LoCoFrag100) for crystallographic screening, with an average cLogP of 0.03 (median 0.23) and an average of £20/g for each compound, facilitating assembly in any laboratory. Formatted in a 10 × 10 matrix to minimize Tanimoto similarity in the 20 cocktails, we demonstrate its applicability on three structurally distinct enzymes involved in microbial cell wall synthesis. Hit rates range from 1 to 6% among these enzymes, with three fragments suggesting avenues for inhibitor exploration. Impact Statement LoCoFrag100 is a low-cost, easily accessible fragment library that enables rapid survey of target ligandability in any laboratory, providing evidence to prioritise targets for follow-up research.

Indexed as

Cell WallDrug DiscoverySmall Molecule LibrariesCrystallography, X-RayLigandsLigandsSmall Molecule Librariescocktailcrystallographyfragment

Identifiers

PMID41532565
PMCPMC13244422

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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.