Evidence map›Paper›PMID 37683649›Full record

ArticleCell chemical biology2024

Profiling of drug resistance in Src kinase at scale uncovers a regulatory network coupling autoinhibition and catalytic domain dynamics.

Sujata Chakraborty, Ethan Ahler, Jessica J Simon, Linglan Fang, Zachary E Potter, Katherine A Sitko, Jason J Stephany, Miklos Guttman, Douglas M Fowler, Dustin J Maly

Abstract read
In one paragraph

Article in Cell chemical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Amino acid substitutions at rheostat positions in the NaProtein science : a publication of the Protein Society · 2025
    Article
  7. Review
  8. Multidrug Resistance: Are We Still Afraid of the Big Bad Wolf.Pharmaceuticals (Basel, Switzerland) · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. All the mutations that are fit to die.Cell chemical biology · 2024
    Article
  17. Article
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

10 authors.

Sujata ChakrabortyDepartment of Chemistry, University of Washington, Seattle, WA 98195, USA.
Ethan AhlerDepartment of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Molecular and Cellular Biology, University of Washington, Seattle, WA 98195, USA.
Jessica J SimonDepartment of Chemistry, University of Washington, Seattle, WA 98195, USA.
Linglan FangDepartment of Chemistry, University of Washington, Seattle, WA 98195, USA.
Zachary E PotterDepartment of Chemistry, University of Washington, Seattle, WA 98195, USA.
Katherine A SitkoDepartment of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Jason J StephanyDepartment of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Miklos GuttmanDepartment of Medicinal Chemistry, University of Washington, Seattle, WA 98195, USA.
Douglas M FowlerDepartment of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA. Electronic address: dfowler@uw.edu.
Dustin J MalyDepartment of Chemistry, University of Washington, Seattle, WA 98195, USA; Department of Biochemistry, University of Washington, Seattle, WA 98195, USA. Electronic address: djmaly@uw.edu.

Funding

Technology to understand genetic variant effects in contextRM1HG010461 · NHGRI · UNIVERSITY OF WASHINGTON · PI Douglas M Fowler, Bruce Colston Trapnell · 2019 to 2026
$18.9M
New Molecular Probes For Protein KinasesR01GM086858 · NIGMS · UNIVERSITY OF WASHINGTON · PI MALY, DUSTIN J · 2008 to 2025
$5.5M
Large-Scale Methods for Assessing the Consequences of Mutations in ProteinsR01GM109110 · NIGMS · UNIVERSITY OF WASHINGTON · PI FOWLER, DOUGLAS M · 2014 to 2021
$2.4M
NHGRI NIH HHS RM1 HG010461NIGMS NIH HHS R01 GM086858NIGMS NIH HHS R01 GM109110
6 · The paper itself

Abstract

Kinase inhibitors are effective cancer therapies, but resistance often limits clinical efficacy. Despite the cataloging of numerous resistance mutations, our understanding of kinase inhibitor resistance is still incomplete. Here, we comprehensively profiled the resistance of ∼3,500 Src tyrosine kinase mutants to four different ATP-competitive inhibitors. We found that ATP-competitive inhibitor resistance mutations are distributed throughout Src's catalytic domain. In addition to inhibitor contact residues, residues that participate in regulating Src's phosphotransferase activity were prone to the development of resistance. Unexpectedly, we found that a resistance-prone cluster of residues located on the top face of the N-terminal lobe of Src's catalytic domain contributes to autoinhibition by reducing catalytic domain dynamics, and mutations in this cluster led to resistance by lowering inhibitor affinity and promoting kinase hyperactivation. Together, our studies demonstrate how drug resistance profiling can be used to define potential resistance pathways and uncover new mechanisms of kinase regulation.

Indexed as

Adenosine Triphosphatesrc-Family KinasesCatalytic DomainDrug ResistancePhosphorylationAdenosine Triphosphatesrc-Family Kinases

Identifiers

PMID37683649
PMCPMC10902203

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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.