Evidence mapPaperPMID 42393339Full record

ArticleMolecular systems biology2026

Paradoxical non-catalytic kinase functions are driven by inhibitor-induced displacement of autoinhibitory domains.

Viviane Reber, Sabrina Keller, Stefanie A Loosli, Yumi Arima, Tatjana Kleele, Paola Picotti, Matthias Gstaiger

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Article in Molecular systems biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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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

7 authors.

Viviane ReberInstitute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-7653-6918
Sabrina KellerInstitute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-8976-9208
Stefanie A LoosliInstitute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0009-0007-2028-8514
Yumi ArimaInstitute of Biochemistry, Department of Biology, ETH Zurich, Zurich, Switzerland.
Tatjana KleeleInstitute of Biochemistry, Department of Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-5320-7337
Paola PicottiInstitute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-4109-3552
Matthias GstaigerInstitute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland. matthias.gstaiger@imsb.biol.ethz.ch.ORCID http://orcid.org/0000-0002-3245-3253

Funding

Innovative Health Initiative (IHI) 875510
6 · The paper itself

Abstract

ATP-competitive kinase inhibitors represent one of the largest classes of targeted anti-cancer drugs. While their primary mechanism is to block catalytic activity, they can also trigger paradoxical phenotypic effects that cannot be explained by catalytic inhibition alone. These observations point to a hidden layer of drug action that modulates non-catalytic kinase functions via changes in kinase conformation and protein-protein interactions (PPIs). Here, we developed a multimodal proteomics approach combining limited proteolysis coupled mass spectrometry on affinity-purified samples (AP-LiP-MS), AP-MS, and proximity labeling-MS to map inhibitor-induced conformation and PPI changes. We show that inhibitor binding causes structural rearrangements in the autoinhibitory domains (AIDs) of all tested kinases, consistent with a transition to an open, active-like kinase conformation. These structural shifts drive distinct kinase-protein interaction changes that control non-catalytic functions: sequestration of AMPK by inhibited CAMKK2 blocks phosphorylation by other kinases, CHEK1 inhibition causes dissociation from the mitochondrial protein CLPB and leads to mitochondrial fragmentation, and structural changes in inhibited PRKCA trigger rapid relocalization to cell junctions. Thus, we identify the ATP-binding site as a major organizing center of kinase conformation and interaction. Our work suggests that these on-target, off-mechanism effects are likely to occur in other kinases as well, and provides the analytical framework to systematically characterize a frequently overlooked phenomenon highly relevant for understanding drug side effects to guide the development of novel therapeutics.

Identifiers

PMID42393339

What Socratic holds

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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 Socratic graph.