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Record W4411923400 · doi:10.1021/acs.jmedchem.5c01204

Covalent Targeting Leads to the Development of a LIMK1 Isoform-Selective Inhibitor

2025· article· en· W4411923400 on OpenAlexfundno aff
Sebastian Mandel, Thomas Hanke, Niall Prendiville, María Baena-Nuevo, Lena M. Berger, Frederic Farges, Martin P. Schwalm, Benedict‐Tilman Berger, Andreas Krämer, Lewis Elson, Hayuningbudi Saraswati, Kamal R. Abdul Azeez, Verena Dederer, Sebastian Mathea, Ana Corrionero, Patricia Alfonso, Sabrina Keller, Matthias Gstaiger, Daniela S. Krause, Susanne Müller, Sandra Röhm, Stefan Knapp

Bibliographic record

VenueJournal of Medicinal Chemistry · 2025
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsnot available
FundersStructural Genomics ConsortiumUniversitätsmedizin der Johannes Gutenberg-Universität MainzGenentechDeutsche KrebshilfeInnovative Medicines InitiativeBundesministerium für Bildung und ForschungDeutschen Konsortium für Translationale KrebsforschungOntario Genomics InstituteGenome CanadaDeutsche ForschungsgemeinschaftDeutsches KrebsforschungszentrumBayerBristol-Myers Squibb FoundationBoehringer Ingelheim
KeywordsChemistryCovalent bondGene isoformCysteineBiochemistrySelectivityEnzymeGene

Abstract

fetched live from OpenAlex

Selectivity for closely related isoforms of protein kinases is a major challenge in the design of drugs and chemical probes. Covalent targeting of unique cysteines is a potential strategy to achieve selectivity for highly conserved binding sites. Here, we used a pan-LIMK inhibitor to selectively probe LIMK1 over LIMK2 by targeting the LIMK1-specific cysteine C349 located in the glycine-rich loop region. Binding kinetics of both noncovalent and covalent LIMK inhibitors were investigated, and the fast on-rate and small size of type-I inhibitors were used in the design of a covalent LIMK1 inhibitor. The developed cell-active, isoform-selective LIMK1 inhibitor showed excellent proteome-wide selectivity in pull-down assays, enabling studies of LIMK1 isoform-selective functions in cellular model systems and providing a versatile chemical tool for studies of the LIMK signaling pathway.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.283
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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Same venueJournal of Medicinal ChemistrySame topicClick Chemistry and ApplicationsFrench-language works237,207