NAPA-ID: a proximity-based system to decode protein-protein interactions
This technology is a compact, robust system that extracts protein-protein and protein-RNA interaction information from diverse samples.
Unmet Need: Decoding protein and RNA interaction networks without cellular engineering
Protein-protein and protein-RNA interactions are central to normal cellular function, and disruptions in these interactions underlie many diseases, including cancer, infectious diseases, and neurological disorders. Existing methods for mapping protein interactomes frequently require genetic modification of cells to express tagged or enzyme-fused versions of the protein of interest. These requirements limit applicability in primary cells, non-dividing or terminally differentiated cells, and clinically relevant samples. There is a need for an interaction-mapping approach that does not rely on engineered expression systems while remaining compatible with established biochemical readouts.
The Technology: Proximity labeling without cell engineering
This technology, termed NAPA-ID, is a targeted proximity-labeling platform that enables molecular profiling around endogenous proteins without requiring genetic modification of the protein or cell engineering. The method uses an affinity-guided APEX-based labeling strategy in fixed and permeabilized cells to selectively mark biomolecules located near a protein of interest. Labeled proteins and RNAs can then be enriched and analyzed by mass spectrometry or sequencing to define the local molecular environment surrounding the target.
By combining target specificity with proximity labeling, NAPA-ID enables characterization of protein-proximal and RNA-proximal molecular neighborhoods across different biological conditions, cell states, or perturbations.
The platform is designed to be broadly adaptable, including for targets or cell systems where endogenous tagging, overexpression, or stable cell-line engineering is impractical.
The technology has been demonstrated in cancer and in stem cells using fixed and permeabilized cells to target endogenous targets such as SRSF2.
Applications:
- Decoding protein-protein interactions for diverse target proteins
- Mapping protein-RNA interactions through proximity labeling strategies
- Drug target identification and mechanism-of-action studies
- Biomarker discovery
- Characterization of protein complexes
- Evaluation of disease-associated or pathogenic mutations on protein complex formation
- Functional analysis of proteins in health and disease
- Research use in primary, non-dividing, or difficult-to-engineer cell types
Advantages:
- Does not require genetic engineering of cells
- Leverages existing antibody reagents for target flexibility
- Compatible with diverse cell types, including primary and terminally differentiated cells
- Integrates with established streptavidin pull-down and proteomics workflows
- Enables rapid target-specific interactome analysis
- Reduces barriers associated with plasmid or vector construction
Lead Inventor:
Tech Ventures Reference:
- IR CU26166
- Licensing Contact: Jerry Kokoshka