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

Background/Objectives: Protein kinase C-δ (PKC-δ) is a pivotal regulator of cellular signalling, and its dysregulation contributes to oncogenesis. While certain isolated PKC-δ domains have been crystallised, the full-length architecture and interdomain interactions remain largely unresolved, limiting mechanistic insight and the design of selective modulators. We aimed to define the full-length, inactive conformation of PKC-δ and identify accessible, functionally relevant binding sites for ligand discovery. Methods: We generated a consensus structural model of full-length inactive PKC-δ using multi-template comparative modelling guided by established inactivity markers. Molecular docking was used to predict ligands targeting the C2 domain, which were subsequently validated in breast cancer cell models, including wild-type and C2 domain-overexpressing lines. Results: Analysis of the model revealed the architecture of the C2/V5 interdomain space, providing a structural rationale for regulation of the nuclear localisation signal (NLS). Docking identified two ligand classes: ligand 1 engaged a C2 domain surface oriented toward the C2/V5 pocket, while ligand 2 targeted the C2 domain phosphotyrosine-binding domain (PTD). Experimental validation in breast cancer cell models demonstrated that both ligands reduced cell viability; ligand 1 showed enhanced effects in C2-overexpressing cells, consistent with predicted accessibility, whereas ligand 2 partially counteracted the C2 domain-induced viability phenotype, likely via interference with PTD-mediated interactions. Conclusions: Full-length structural context is essential for identifying accessible, functionally relevant binding sites and understanding context-dependent kinase regulation. Integrating computational modelling with phenotypic validation establishes a framework for selective PKC-δ modulation, offering insights to guide ligand discovery, improve isoform selectivity, and inform strategies to mitigate kinase inhibitor resistance in precision oncology.