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Modelling the Full-Length Inactive PKC-δ Structure to Explore Regulatory Accessibility and Selective Targeting

Rasha Khader1,2, Lodewijk V Dekker1

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|November 27, 2025
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Structural modeling of full-length inactive protein kinase C-δ (PKC-δ) identified novel binding sites. This research provides a framework for developing targeted therapies against cancer by enabling selective PKC-δ modulation.

Keywords:
breast cancercomparative modellingkinase regulationligand dockingprotein kinase C-δ

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Cancer Biology

Background:

  • Protein kinase C-δ (PKC-δ) is crucial in cell signaling and implicated in cancer development.
  • The complete structure and interactions of PKC-δ are not well understood, hindering the development of targeted drugs.
  • Understanding PKC-δ's inactive state is key for designing selective modulators.

Purpose of the Study:

  • To determine the full-length inactive structure of PKC-δ.
  • To identify accessible binding sites on PKC-δ for drug discovery.
  • To provide a structural basis for PKC-δ regulation and modulation.

Main Methods:

  • Generated a consensus structural model of inactive, full-length PKC-δ using comparative modeling.
  • Employed molecular docking to predict ligands targeting the C2 domain.
  • Validated ligand effects in breast cancer cell models, including those with C2 domain overexpression.

Main Results:

  • The structural model elucidated the C2/V5 interdomain architecture and its role in regulating the nuclear localization signal (NLS).
  • Two distinct ligand classes were identified: one binding to the C2 domain surface near the C2/V5 pocket, and another targeting the C2 domain phosphotyrosine-binding domain (PTD).
  • Both ligands reduced cancer cell viability, with ligand 1 showing enhanced efficacy in C2-overexpressing cells and ligand 2 partially reversing C2 domain-induced effects.

Conclusions:

  • Full-length structural information is vital for discovering functional binding sites and understanding context-dependent kinase regulation.
  • Integrating computational modeling with experimental validation offers a pathway for selective PKC-δ modulation.
  • This approach can guide drug discovery, enhance isoform selectivity, and inform strategies against kinase inhibitor resistance in oncology.